
Publications in Refereed Journals
Books
J. Li, C.M. Woodside, J.W. Chinneck, M. Litoiu (2017), "Adaptive Cloud Deployment using Persistence Strategies and Application Awareness", IEEE Transactions on Cloud Computing, vol. 5, no. 2, pp. 277290 (http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7064811). We modify our earlier CloudOpt method for task deployment in clouds to handle dynamic changes in workload using penalties and rewards to encourage stable deployments and discourage thrashing.
A.U. Chaudhry, R.H.M. Hafez, J.W. Chinneck (2016), “Realistic InterferenceFree Channel Assignment for Dynamic Wireless Mesh Networks Using Beamforming”, Ad Hoc Networks, vol. 51, pp. 2135. Available online at http://www.sciencedirect.com/science/article/pii/S1570870516301937 This paper develops the first channel assignment method for wireless mesh networks that incorporates beamforming in the conflict graph and matrix. This reduces the number of channels required significantly.
A.U. Chaudhry, J.W. Chinneck, R.H.M. Hafez (2016), “Fast Heuristics for the Frequency Channel Assignment Problem in MultiHop Wireless Networks”, European Journal of Operational Research, vol. 251, pp. 771782, DOI: http://dx.doi.org/10.1016/j.ejor.2015.12.016. Channel assignment in wireless networks can be cast as a minimum colouring problem, but this does not account for cumulative interference. We develop fast algorithms for this extended colouring problem that are orders of magnitude faster than an exact solution method while consistently returning nearoptimum results.
A.U. Chaudhry, R.H.M. Hafez, and J.W. Chinneck (2015), “On the Impact of Interference Models on Channel Assignment in MultiRadio MultiChannel Wireless Mesh Networks,” Ad Hoc Networks, vol. 27, pp. 6880. The interference model assumed in channel assignment significantly affects the results. More frequency channels are needed when the interference model is more realistic than commonly assumed.
W. Ibrahim, M. Shousha, J.W. Chinneck (2015), “Accurate and Efficient Estimation of Logic Circuits Reliability Bounds”, IEEE Transactions on Computers, vol. 64, no. 5, pp. 12171229. We develop a method to estimate the reliability bound for large and complex circuits. The method is fast and highly accurate in finding the set of input values that produces the lowest reliability.
A.U. Chaudhry, J.W. Chinneck and R.H.M. Hafez (2013), “On the Number of Channels Required for Interferencefree Wireless Mesh Networks”, EURASIP Journal on Wireless Communications and Networking 2013:229 (14 September 2013). Online at http://jwcn.eurasipjournals.com/content/2013/1/229. We develop a method for assigning channels in a wireless mesh network so that throughput is maximized, there is no interference, and the number of distinct channels is small.
H. Mahmoud and J.W. Chinneck (2013), "Achieving MILP Feasibility Quickly Using General Disjunctions", Computers and Operations Research, vol. 40, no. 8, pp. 20942102. Preprint version. Appendix. We show that oblique disjunctions that branch on linear combinations of variables can reduce the time to find the first integerfeasible solution in hard mixedinteger linear programs. We develop new ways to construct the general disjunctions and methods for deciding when they should be used.
L. Smith, J.W. Chinneck, and V. Aitken (2013), “Constraint Consensus Concentration for Identifying Disjoint Feasible Regions in Nonlinear Programs”, Optimization Methods and Software, vol. 28, no. 2, pp. 339–363. Preprint version. There may be multiple disjoint feasible regions in a constrained nonlinear program. We improve on multistart methods for global optimization by using Constraint Consensus to quickly explore the variable space to find the feasible regions before launching an expensive local solver. Our solutions are more efficient because we usually launch the local solver only once near each feasible region.
L. Smith, J.W. Chinneck, V. Aitken (2013), “Improved Constraint Consensus Methods for Seeking Feasibility in Nonlinear Programs”, Computational Optimization and Applications, vol. 54, no. 3, pp. 555578. DOI: http://dx.doi.org/10.1007/s105890129473z. Preprint version. We develop several improvements to the Constraint Consensus method for quickly finding nearfeasible points in nonlinear programs: (i) a simple new way of constructing the consensus vector, (ii) a predictorcorrector method, (iii) a better way of selecting the output point, and (iv) better ways of selecting the subset of violated constraints to operate on at each iteration, which is especially effective when used in conjunction with barrier method local solvers. We also investigate quadratic feasibility vectors.
M. StHilaire, J.W. Chinneck, S. Chamberland, and S. Pierre (2012), “Efficient Solution of the 3G Network Planning Problem”, Computers and Industrial Engineering, vol. 63, no. 4, pp. 819–830. DOI: http://dx.doi.org/10.1016/j.cie.2012.05.004 We compare MIP and heuristic approaches for solving a difficult mobile telecommunications planning problem.
J.W. Chinneck (2012), "Integrated Classifier Hyperplane Placement and Feature Selection", Expert Systems with Applications, vol. 39, no. 9, pp. 81938203. Preprint version. Feature reduction and binary classifier hyperplane placement are normally treated as two distinct and separate processes. This paper combines the two using algorithms for solving the maximum feasible subset problem for a set of linear constraints. The method alternates between making progress on placing the separating hyperplane and adding or removing features. The empirical results are very good.
J. Pryor and J.W. Chinneck (2011), “Faster IntegerFeasibility in MixedInteger Linear Programs by Branching to Force Change”, Computers and Operations Research, vol. 38, pp. 1143–1152. Preprint version. Surprisingly, it turns out that if you want to reach a feasible solution for a MIP quickly, you should select branches that have the lowest probability of returning a feasible solution! This is because branching this way forces many other candidate variables to change their values simultaneously.
D.T. Wojtaszek and J.W. Chinneck (2010), “Faster MIP Solutions via New Node Selection Rules”, Computers and Operations Research, vol. 37, no. 9, pp. 15441556. Preprint version. DOI: http://dx.doi.org/10.1016/j.cor.2009.11.011 available online here. New heuristics for use in mixedinteger linear programming to determine when to backtrack, and which node to choose when backtracking, based on correlations and patterns commonly found in MIP solutions. Significantly improved solution speeds are demonstrated.
W. Ibrahim and J.W. Chinneck (2008), "Improving Solver Success in Reaching Feasibility for Sets of Nonlinear Constraints", Computers and Operations Research, Vol. 35, pp. 13941411 (available online October 2, 2006 at www.sciencedirect.com). Preprint version in pdf. An improved initial point placement heuristic, coupled with the Constraint Consensus algorithm for point improvement provides starting points that greatly increase the success of various nonlinear solvers in reaching feasibility.
J. Patel and J.W. Chinneck (2007), "ActiveConstraint Variable Ordering for Faster Feasibility of Mixed Integer Linear Programs", Mathematical Programming Series A, vol. 110, pp. 445474. (pdf) You can reach feasibility for MIPs much faster by selecting the branching variable based on its impact on the active constraints in the parent LP relaxation, instead of using the traditional approach of selecting the branching variable based on its impact on the objective function.
J.W. Chinneck (2004), "The Constraint Consensus Method for Finding Approximately Feasible Points in Nonlinear Programs", INFORMS Journal on Computing, vol. 16, no. 3, pp. 255265. (pdf) A fast algorithm for finding approximately feasible points from initial points that are at extreme distances from the feasible region.
S. Chao, J.W. Chinneck, and R.A. Goubran (2004), "Assigning Service Requests in VoiceoverInternet Gateway Multiprocessors", Computers and Operations Research, vol. 31, no. 14, pp. 24192437. Article available through ScienceDirect. An online binpacking approach improves the efficiency of call processing significantly.
Walid Ibrahim, John W. Chinneck and Shalini Periyalwar (2003), "A QoSbased Charging and Resource Allocation Framework for Next Generation Wireless Networks", Wireless Communications and Mobile Computing, vol. 3, no. 7, pp. 895906.
J.W. Chinneck, V. Pureza, R.A. Goubran, G.M. Karam, M. Lavoie (2003), "A Fast TasktoProcessor Assignment Heuristic for RealTime Multiprocessor DSP Applications", Computers & Operations Research, vol. 30, no. 5, pp. 643670. (Publishers Web page, full text available to subscribers).
J.W. Chinneck (2002), "Discovering the Characteristics of Mathematical Programs via Sampling", Optimization Methods and Software, vol. 17, no.2, pp. 319352. (pdf of draft version) Related to the MProbe project.
J.W. Chinneck (2001), "Analyzing Mathematical Programs using MProbe", Annals of Operations Research vol. 104, pp. 3348. (pdf of draft version) Download the latest version of MProbe from here.
J.W. Chinneck (2001), "Fast Heuristics for the Maximum Feasible Subsystem Problem", INFORMS Journal on Computing, vol. 13, no. 3, pp. 210223. (pdf) Useful in analyzing infeasible linear programs, but also for hyperplane placement in data classification (examples are given), etc.
J.W.Chinneck and K. Ramadan (2000), "Linear Programming with Interval Coefficients", Journal of the Operational Research Society, vol. 51, pp. 209220. If the coefficients of your linear program are only approximately known, then how can you solve the LP? We present a method for finding the best optimum and the worst optimum when the coefficients are only known within specified intervals.
O. Guieu and J.W. Chinneck (1999), "Analyzing Infeasible MixedInteger and Integer Linear Programs", INFORMS Journal on Computing, vol. 11, no. 1, pp. 6377. (pdf)
P.R. Larijani, J.W. Chinneck, R.H. Hafez (1998), "Nonlinear Power Assignment in Multimedia CDMA Wireless Networks", IEEE Communications Letters, vol. 2, no. 9, pp. 251253.
R. Awad and J.W. Chinneck (1998), "Proctor Assignment at Carleton University", Interfaces, vol 28, no. 2, pp. 5871. Describes a hybrid genetic algorithm to solve a complex problem of assigning final examination proctors. (pdf)
E.W. Dravnieks and J.W. Chinneck, (1997), "Formulation Assistance for Global Optimization Problems", Computers and Operations Research, vol 24, no.2, pp. 11511168.
J.W. Chinneck, (1997), "Finding a Useful Subset of Constraints for Analysis in an Infeasible Linear Program", INFORMS Journal on Computing , vol. 9, no. 2. There are now several algorithms for isolating Irreducible Infeasible Subsets (IISs) of constraints in an infeasible LP. However, some combinations of algorithms find IISs that are easier for humans to interpret... (PDF: 948 kbytes)
J.W. Chinneck, (1996) "Localizing and Diagnosing Infeasibilities in Networks", ORSA Journal on Computing, Vol. 8, No. 1, pp. 5562. (pdf)
J.W. Chinneck, (1996), "Computer Codes for the Analysis of Infeasible Linear Programs ", Journal of the Operational Research Society, Vol. 47, pp. 6172. Gives an overview of algorithms for analyzing infeasible LPs, and compares the effectiveness of different computer codes in analyzing infeasibility. Includes several commercial codes.
J.W. Chinneck, (1996), "An Effective PolynomialTime Heuristic for the MinimumCardinality IIS SetCovering Problem", Annals of Mathematics and Artificial Intelligence, vol. 17, pp. 127144. Despite the title, this paper is about finding the smallest number of constraints to remove from an infeasible LP such that the remaining set of constraints is feasible. This is the same as finding the maximum cardinality feasible subset of constraints from among the original infeasible set. The problem is NPcomplete, but the paper describes a remarkably effective polynomialtime heuristic. This has some surprising applications, including a way to train neural networks, and to linearly classify data.
J.W. Chinneck and R.H.H. Moll, (1995). "Processing Network Models for Forest Management", OMEGA, vol. 23, no. 5, pp. 499510.
J.W. Chinneck, (1995), "Processing Network Models of Energy/Environment Systems", Computers and Industrial Engineering, vol. 28, no. 1, pp. 179189.
J.W. Chinneck, (1995), "Analyzing Infeasible Nonlinear Programs", Computational Optimization and Applications, vol. 4, no.2, pp. 167179.
J.W. Chinneck, (1994), "MINOS(IIS): Infeasibility Analysis Using MINOS", Computers and Operations Research, Vol. 21, No. 1, pp. 19. You can download the latest version of MINOS(IIS) from here.
M.W. Carter, G. Laporte, J.W. Chinneck (1994), "A General Examination Scheduling System", Interfaces, Vol. 24, No. 3, pp. 109120. (PDF)
R.H.H. Moll, and J.W. Chinneck, (1992), "Modeling Regeneration and Pest Control Alternatives for a Forest System in the Presence of Fire Risk", Natural Resource Modelling, Vol. 6, No. 1, pp. 2349.
J.W. Chinneck, (1992), "Viability Analysis: A Formulation Aid for All Classes of Network Models", Naval Research Logistics, Vol. 39, pp. 531543. Nonviable network models have a peculiar property: some arc flows are forced to zero, not by added flow bounds, but by the structure of the network model itself. This paper and its earlier companion describe ways to find and diagnose such problems.
J.W. Chinneck and E.W. Dravnieks, (1991), "Locating Minimal Infeasible Constraint Sets in Linear Programs", ORSA Journal on Computing, Vol. 3, No. 2, pp. 157168. My earliest and widely referenced paper on finding Irreducible Infeasible Subsets (IISs) of constraints in infeasible LPs. For a review of the current state of the art in infeasibility analysis, see the chapter on "Feasibility and Viability" (listed under Book Chapters, below). (pdf: 978 kbytes)
J.W. Chinneck, (1990), "Formulating Processing Networks: Viability Theory", Naval Research Logistics, Vol. 37, pp. 245261.
J.W. Chinneck, (1988), "Industrial Application of a SecondLaw Modelling Procedure", Trans. of the CSME, Vol.12, No.3, pp.153157.
J.W. Chinneck and M. Chandrashekar, (1984), "Models of LargeScale Industrial Energy Systems. Part II: Optimization and Synthesis", Energy  The International Journal, Vol.9, No.8, pp.679692.
J.W. Chinneck and M. Chandrashekar, (1984), "Models of LargeScale Industrial Energy Systems. Part I: Simulation", Energy  The International Journal, Vol.9, No.1, pp.2134.
K.G.T. Hollands, J.W. Chinneck and M. Chandrashekar, (1979), "Collector and Storage Efficiencies in Solar Heating Systems", Solar Energy, Vol.23, pp.471478.
J.W. Chinneck, B. Kristjansson, and M. Saltzman (eds.) (2009), "Operations Research and CyberInfrastructure", Operations Research / Computer Science Interfaces, ISBN 9780387888422, Springer Science+Business Media, LLC (2009). Springer. Amazon.com. Amazon.ca.
J.W. Chinneck (2008), "Feasibility and Infeasibility in Optimization: Algorithms and Computational Methods", Vol. 118, International Series in Operations Research and Management Sciences, ISBN 9780387749310, Springer. Table of Contents. Publishers web page. Amazon.com. Amazon.ca. Review in the ICS Newsletter Spring 2008. Review Excerpt from MathDL.
J.W. Chinneck (2000), "Practical Optimization: a Gentle Introduction", online textbook, see http://www.sce.carleton.ca/faculty/chinneck/po.html.
John W. Chinneck, Michel Nakhla, and Q.J. Zhang (2004). "ComputerAided Design for Electrical and Computer Engineering" in H.J. Greenberg (ed.) Tutorials On Emerging Methodologies And Applications In Operations Research, pp. 61 to 644, Springer, New York. An introduction to the many applications of operations research in computeraided design of microelectronic devices, and a survey of techniques developed by the CAD community that are of interest to operations researchers.
J.W. Chinneck, (1997), "Feasibility and Viability" in Advances in Sensitivity Analysis and Parametric Programming, T. Gal and H.J. Greenberg (eds.), Kluwer Academic Publishers, International Series in Operations Research and Management Science, Vol. 6. This article provides an overview of the stateofthe art in analyzing infeasible (and nonviable) mathematical programs of all types. A good starting point if you are new to infeasibility analysis. Publisher info.
J.W. Chinneck and W. Michalowski, (1996), "MOLP Formulation Assistance Using LP Infeasibility Analysis", in MultiObjective Programming and Goal Programming: Theories and Applications, M. Tamiz (ed.), Lecture Notes in Economics and Mathematical Systems, vol. 432, SpringerVerlag.
J.W. Chinneck (2009), Guest Editor, INFORMS Journal on Computing, Special Cluster on HighThroughput Optimization, vol. 21, no. 3, Summer 2009. Foreword pp. 347–348.
J.W. Chinneck (2008), Guest Editor, Computers and Operations Research Special Issue on Algorithms and Computational Methods in Feasibility and Infeasibility, vol. 35. Foreword pp. 13771378 (available online 2006).
J.W. Chinneck (2006), Guest Editor, INFORMS Journal on Computing Special Cluster on Operations Research in Electrical and Computer Engineering, vol. 18, no. 2, Spring 2006.
J.W. Chinneck (2002), Guest Editor, INFORMS Journal on Computing Special Issue on the Merging of Mathematical Programming and Constraint Programming, vol. 14, no. 4, Fall 2002.
J.W. Chinneck, and M.A. Saunders, (1995), "MINOS(IIS) Version 4.2: Analyzing Infeasibilities in Linear Programs", European Journal of Operational Research, vol. 81, pp. 217218.
J.W. Chinneck, (1990), "VIABLE1Code for Identifying Nonviabilities in Processing Network Models", European Journal of Operational Research, Vol. 44, pp. 119120.
J.W. Chinneck, (1985), "On Systems Theory and Models of Heat Flow", IEEE Trans. on Systems, Man and Cybernetics, Vol.SMC15, No.3, pp.423426.
A.U. Chaudhry, R.H.M. Hafez, and J.W. Chinneck (2015), “On the Performance of Beamformingbased Channel Assignment in Dense Wireless Mesh Networks”, the 28^{th} Canadian Conference on Electrical and Computer Engineering, Halifax, Canada, May 36.
A.U. Chaudhry, R.H.M. Hafez, and J.W. Chinneck (2014), “Significantly Reducing the Number of Frequency Channels Required for Wireless Mesh Networks using Beamforming”, IEEE Wireless Communications and Networking Conference WCNC 2014, Istanbul, Turkey, April 69.
J.W. Chinneck, M. Litoiu, C.M. Woodside (2014), “RealTime MultiCloud Management Needs Application Awareness”, 5^{th} ACM/SPEC International Conference on Performance Engineering ICPE 2014, Dublin, Ireland, March 2226.
A.U. Chaudhry, J.W. Chinneck, and R.H.M. Hafez (2013), “Channel Requirements for Interferencefree Wireless Mesh Networks to Achieve Maximum Throughput”, ICCCN 2013, Nassau, Bahamas, July 30  August 2.
Z. Li, C.M. Woodside, J.W. Chinneck, M. Litoiu (2011). "CloudOpt: MultiGoal Optimization of Application Deployments across a Cloud", 7th International Conference on Network and Service Management (CNSM 2011), October 2428, Paris, France.
Z. Li, J.W. Chinneck, C.M. Woodside, M. Litoiu (2009), “Deployment of Services in a Cloud Subject to Memory and License Constraints”, 2009 IEEE Second International Conference on Cloud Computing (CLOUDII 2009), Bangalore, India, September 2125.
Z. Li, J.W. Chinneck, C.M. Woodside, M. Litoiu, and G. Iszlai (2009), “Performance Model Driven QoS Guarantees and Optimization in Clouds”, CLOUD 2009, 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing, Vancouver, May 23, in conjunction with the 2009 IEEE 31st International Conference on Software Engineering (ICSE 2009), May 16–24.
Z. Li, J.W. Chinneck, C.M. Woodside, M. Litoiu (2009), "Fast Scalable Optimization to Configure Service Systems having Cost and Quality of Service Constraints”, the 6th International Conference on Autonomic Computing and Communications (ICAC 2009), Barcelona, June 1519.
J.W. Chinneck (2009), "Tailoring Classifier Hyperplanes to General Metrics", in J.W. Chinneck, B. Kristjansson, M. Saltzman (eds.) "Operations Research and CyberInfrastructure", Springer Science+Media LLC.
W. Ibrahim, J.W. Chinneck, H. ElSayed (2005), "QoS Satisfaction Based Charging and Resource Management Policy for Next Generation Wireless Networks", IEEE WirelessCom 2005, Maui, Hawaii, June 1316.
M.W. Carter, G. Laporte, and J.W. Chinneck, (1993), "An Introduction to EXAMINE: A Flexible Examination Scheduling System", Proceedings of the 79th AACRAO Annual Meeting, April 1721, Orlando.
R.G. Brown, J.W. Chinneck and G.M. Karam, (1989) "Optimization with Constraint Programming Systems", Proceedings of "Impact of Recent Computer Advances on Operations Research", Williamsburg, Virginia, January 46. R. Sharda et al. (eds.), Publications in Operations Research Series, No.9, Elsevier Science Publishers, pp. 463473.
J.W. Chinneck, S.C. Carpenter, and E.C. Shewen, (1982), "A Study of Methods of Improving the Performance of Solar Water Walls", Proceedings of the Energex Conference, Regina, August 2329.
M. Chandrashekar, J.W. Chinneck and F.C. Wong, (1978), "SystemTheoretic Models for Analysis of ProductionConsumption Systems", Proceedings of the Second International Symposium on Large Engineering Systems, Waterloo, Ontario.
A. Scheer and J.W. Chinneck (2015), “Efficient Isolation of Irreducible Infeasible Subsets in MixedInteger Linear Programs”, Mixed Integer Programming Workshop, Chicago, June 14.
H.A. Mahmoud and J.W. Chinneck (2011), "Achieving Integer Feasibility Quickly by Alternating AxisParallel and General Disjunctions", 2011 Mixed Integer Programming Workshop, University of Waterloo, Waterloo, Canada, June 2023.
H.A. Mahmoud and J.W. Chinneck (2010), “Achieving Integer Feasibility Quickly by Alternating AxisParallel and General Disjunctions”, 2010 Mixed Integer Programming Workshop, Georgia Institute of Technology, Atlanta, Georgia, July 2629.
J. Chinneck and R. Sharda (2011), "Computer Science and Operations Research Interfaces," Encyclopedia of Operations Research/Management Science, 2nd edition, forthcoming.
J.W. Chinneck (1998), "Improved Linear Classification via LP Infeasibility Analysis", Dept. of Systems and Computer Engineering Technical Report SCE9809. Permits the placement of classification lines that tend to minimize the number of misclassified points (as opposed to a measure of the misclassification distance).
Z. You, J.W. Chinneck and C.M. Woodside, (1993), "Localizing Problems for Structural Debugging of Petri Net Models", Department of Systems and Computer Engineering Technical Report, SCE9327.
Z. You, J.W. Chinneck and C.M. Woodside (1993), "Modular Structural Debugging of Large Petri Net Models", Department of Systems and Computer Engineering Technical Report SCE9328.
J.W. Chinneck (1993). "Finding Minimal Infeasible Sets of Constraints in Infeasible Mathematical Programs", Systems and Computer Engineering Technical Report SCE9301.
J.W. Chinneck (1993), "MINOS(IIS) 4.2 User's Manual", Systems and Computer Engineering Technical Report SCE9317.
Z. You, J.W. Chinneck and C. M. Woodside, (1992). "Prescreening and Localization of Petri Nets Model Errors by Viability Analysis", Systems and Computer Engineering Technical Report.
R.G. Brown, G.M. Karam and J.W. Chinneck, (1991), "An Extensible Constraint Solver Architecture", Department of Systems and Computer Engineering Technical Report SCE9141.
J.W. Chinneck, R.A. Goubran, G.M. Karam and M. Lavoie, (1990), "A Design Approach for RealTime Multiprocessor DSP Applications", Department of Systems and Computer Engineering Technical Report SCE9005.
J.W. Chinneck, R.A. Goubran, G.M. Karam, M. Lavoie and S. Kerr, (1990), "Graphical Interface for Multiprocessor RealTime Digital Signal Processing Design", report to the Defence Research Establishment Pacific, March. Includes software and software documentation manuals.
A. Sankaranarayanan, J.W. Chinneck, and M. Chandrashekar (1986), "Photovoltaic Powered Pumping Systems: Final Report", report to the Solar Energy Program, National Research Council, March.
J.W. Chinneck, (1984), "Assessment of a New Procedure for Modelling Industrial Energy Systems", report to the Office of Energy Research and Development, Energy Mines and Resources Canada, August.
M. Chandrashekar, J.W. Chinneck, and A. Sankaranarayanan, (1984), "Photovoltaic Powered Water Pumping Systems  Availability and Performance. Milestone Report I: Technical Literature and Computer Model Survey", report to the Solar Energy Program, National Research Council, June.
J.W. Chinneck and S.C. Carpenter, (1983), "Review of the ENERSAVE Industrial and Commercial Energy Audit Computer Program. Phase II: Proposed Improvements", report to the Energy Conservation and Oil Substitution Branch, Energy Mines and Resources Canada, March.
S.C. Carpenter and J.W. Chinneck, (1982), "Review of the ENERSAVE Industrial and Commercial Energy Audit Computer Program. Phase I: Preliminary Assessment", report to the Conservation and Renewable Energy Branch, Energy Mines and Resources Canada, March.
S.C. Carpenter, E.C. Shewen and J.W. Chinneck, (1982), "Feasibility Study for a High Performance Solar Water Wall", report to the Solar Energy Program, Energy Mines and Resources Canada, May.
J.W. Chinneck, (1982), "The Steel Plant Energy Model, Volume 2: Guide to the Input Data", report to the Energy Management Group, The Algoma Steel Corporation Limited, March.
J.W. Chinneck, (1981), "The Steel Plant Energy Model, Volume 1: Structure of the Model", report to the Energy Management Group, The Algoma Steel Corporation Limited, May.
J.W. Chinneck, E.C. Shewen and M. Chandrashekar, (1979), "WATSUNIII Solar Heating and Economic Evaluation Program Documentation", report to the Division of Building Research, National Research Council of Canada.
K.G.T. Hollands, J.W. Chinneck and M. Chandrashekar (1977), "A Method of Rating and Sizing Solar Collectors in Residential Heating Systems", University of Waterloo Research Institute Report No.7703.
J.W. Chinneck, M. Shafique (2016), “A Fast Heuristic for Global Optimization”, INFORMS, Nashville, November 1216.
J.W. Chinneck, E. Klotz, and A. Scherr (2016), “Improved Analysis of Infeasible MixedInteger Linear and Quadratic Programs”, INFORMS, Nashville, November 1216.
J.W. Chinneck (2016), “MILP Insights and Algorithms”, COCANA Seminar Series, UBC Okanagan, Kelowna, October 27 (invited).
J.W. Chinneck (2016), “Projection Methods and Nonlinear Constraint Shape”, EURO 2016, Poznan, Poland, July 36.
J.W. Chinneck (2016), “Projection Methods and Nonlinear Constraint Shape”, Optimization Days, Montreal, May 24.
J.W. Chinneck, M. Shafique (2015), “A Fast Heuristic Global Optimizer”, INFORMS, Philadelphia, November 14.
J.W. Chinneck, A. Scherr (2015), “Faster Infeasibility Analysis for Mixed Integer Linear Programming”, INFORMS, Philadelphia, November 14.
J.W. Chinneck (2015), "MILP Insights and Algorithms", Lehigh University Department of Industrial and Systems Engineering, department seminar, September 29 (invited).
J.W. Chinneck, M. Shafique (2015), "CCGO: A Fast Heuristic Global Optimizer”, ISMP, Pittsburgh, July 1217.
M. Shafique, J.W. Chinneck (2015), "CCGO: Fast Heuristic Global Optimization", CORS/INFORMS, Montreal, June 1417.
J.W. Chinneck, S. Ernst (2014), “New Parallel Programming Languages for Optimization Research”, INFORMS, San Francisco, November 912. We compare Google’s Go language with Julia for use in optimization research.
J.W. Chinneck and M. Shafique (2014). "A Fast Heuristic for Global Optimization and MINLP", INFORMS, San Francisco, November 912.
J.W. Chinneck, M. Shafique (2014), "A Heuristic Method for MINLP", MINLP 2014, CarnegieMellon University, Pittsburgh, June 25.
M. Shafique, J.W. Chinneck (2014), "A Fast Heuristic for Global Optimization and MINLP", CORS, Ottawa, May 2628.
R. Kaur, J.W. Chinneck, C.M. Woodside (2014), " Task Assignment Across Clouds by Graph Partitioning", CORS, Ottawa, May 2628.
D.W. Hawker, C.M. Woodside, J.W. Chinneck (2014), "Simulating Task Assignment Policies in an EdgeCore Cloud Architecture", CORS, Ottawa, May 2628.
A. Chaudhry, J.W. Chinneck, R. Hafez (2014), "Frequency Channel Requirements for InterferenceFree Wireless Mesh Networks", CORS, Ottawa, May 2628.
J.W. Chinneck (2014), “Experiments in Using Google's Go Language for Optimization Research”, Optimization Days, Montreal, May 57.
J.W. Chinneck, M. Shafique (2013), “A Fast Heuristic Method for Global Optimization and MINLP”, INFORMS, Minneapolis, October 59.
J.W. Chinneck (2013), “Branching to Force Variable Value Propagation in MILP”, Workshop on Seeking Feasibility in Combinatorial Problems at CPAIOR 2013, Yorktown Heights, May 1822 (pdf).
J.W. Chinneck and M. Shafique (2013), “Towards a Fast Heuristic for Global Optimization and MINLP”, CPAIOR 2013, Yorktown Heights, May 1822.
M. Shafique and J.W. Chinneck (2013), “Heuristic Global Optimization via Quick Exploration of the Variable Space”, Optimization Days, Montreal, May 68.
J.W. Chinneck (2013), “Integrated Hyperplane Placement and Feature Selection”, ICS 2013, Santa Fe, January 68.
J.W. Chinneck and H. Mahmoud (2012), “Fast MILP Feasibility Using General Disjunctions” INFORMS, Phoenix, October 1317.
J.W. Chinneck, A. Holder, K. Aardal, R. Fourer, S. Raghavan, E. Wasil, D. Woodruff (2012), “How to Publish your Paper in The INFORMS Journal on Computing”, INFORMS, Phoenix, October 1317.
J.W. Chinneck (2012), "Integrated Hyperplane Placement and Feature Selection", CORS, Niagara Falls, Ontario, June 1113.
J.W. Chinneck, L. Smith, V. Aitken (2012), "Better Placement of Local Solver Launch Points for Global Optimization", CORS, Niagara Falls, Ontario, June 1113.
J.W. Chinneck (2012), "Recent Advances in MixedInteger Linear Programming", Optimization Days, Montreal, May 69. Invited one hour plenary. Slides in pdf.
J.W. Chinneck, J. Pryor (2011), "Faster Integer Feasibility in MIPs by Branching to Force Change", INFORMS, Charlotte, November 1316.
J.W. Chinneck, L. Smith, V. Aitken (2011), "Better Placement of Local Solver Launch Points for Global Optimization", INFORMS, Charlotte, November 1316.
J.W. Chinneck (2011), “Branching in MixedInteger Linear Programming”, CPAIOR 2011, Berlin, May 2327 (invited 75 minute tutorial). Slides in pdf on conference website. Youtube video of the tutorial.
J.W. Chinneck and J. Pryor (2011), "Faster Integer Feasibility in MIPs by Branching to Force Change", GERAD seminar, Ecole Polytechnique, Montreal, February 16.
J.W. Chinneck and J. Pryor (2011), "Faster Integer Feasibility in MIPs by Branching to Force Change", INFORMS Computing Society Conference, Monterey, January 911.
J.W. Chinneck and J. Pryor (2011), "Faster Integer Feasibility in MIPs by Branching to Force Change", seminar series, Department of Econometrics and Operations Research, Tilburg University, Tilburg Netherlands, January 5.
H. Mahmoud and J.W. Chinneck (2010), “Achieving Integer Feasibility Quickly by Alternating AxisParallel and General Disjunctions”, INFORMS, Austin, Texas, November 710.
J.W. Chinneck and J. Pryor (2010), “Faster Integer Feasibility in MIPs by Branching to Force Change, Austin, Texas, November 710.
T. Harrison, J. Camm, J.W. Chinneck, M. Gendreau, S. Graves (2010), “Panel Discussion with INFORMS Editors, Austin, Texas, November 710.
J.W. Chinneck (2010), "Heuristics for Feasibility and Optimality in MixedInteger Programming", full day of presentations in conjunction with Andrea Lodi (University of Bologna, Italy) at the CIRRELT Spring School on Combinatorial Optimization in Logistics, University of Montreal, May 17 (invited). Slides in pdf.
J.W. Chinneck and J. Pryor (2010), "Faster Integer Feasibility in MIPs by Branching to Force Change", Operations Research Department seminar series, Naval Postgraduate School, Monterey, California, April 22 (invited).
J.W. Chinneck and L. Smith (2009), “Variable Space Exploration in LargeScale NLP”, INFORMS, San Diego, October 1114.
J.W. Chinneck and J. Pryor (2009), “A Study of MIP Branching Direction Heuristics”, International Symposium on Mathematical Programming ISMP 2009, Chicago, August 2328.
J.W. Chinneck (2009), “Tailoring Classifier Hyperplanes to General Metrics”, ICS 2009, Charleston, South Carolina, January 1113.
D.T. Wojtaszek and J.W. Chinneck (2008), “New MIP Node Selection Heuristics”, INFORMS Washington D.C., October 1215.
D.T. Wojtaszek and J.W. Chinneck (2008), “Faster MIP Solutions via New Node Selection Rules” CORS/Optimization Days, Quebec City, May 1214.
J.W. Chinneck (2008). A series of talks for Microsoft, Redmond, Washington, April 2325 (invited):
J.W. Chinneck (2008), “The Maximum Feasible Subsystem Problem and Applications”, Industrial Optimization Seminar, the Fields Institute, Toronto, February 5 (invited). Slides and audio.
J.W. Chinneck (2007), "Connecting with the Academic World", DRDC, Department of National Defence, December 6.
D. Wojtaszek and J.W. Chinneck (2007), "Faster MIP Solutions via New Node Selection Rules", INFORMS Seattle, November 47.
J.W. Chinneck, W. Ibrahim, M. MacLeod (2007), "Fast NLP Feasibility via Constraint Consensus Methods", ICCOPTII/MOPTA'07, Hamilton, Canada, August 1316.
J. W. Chinneck (2007), "Feasibility and Infeasibility in Optimization", CPAIOR07 conference, Brussels May 2326. Invited tutorial (1.5 hours). Pdf.
J.W. Chinneck and M. MacLeod (2007), "Multistart Constraint Consensus for Seeking Feasibility in Nonlinear Programs", CORS, London, Ontario, May 1416.
J.W. Chinneck (2007), "Reaching Feasibility Quickly in MixedInteger Programs. Part I: Tutorial on the State of the Art", Optimization Days 2007, May 79, Montreal.
J.W. Chinneck (2007), "Reaching Feasibility Quickly in MixedInteger Programs. Part II: New Branching Heuristics", Optimization Days 2007, May 79, Montreal.
D.T. Wojtaszek and J.W. Chinneck (2007), "Faster MIP Solutions via New Node Selection Rules" , Optimization Days 2007, May 79, Montreal.
J.W. Chinneck (2007), "Algorithms for the Maximum Feasible Subset Problem", Operations Research Department seminar series, Naval Postgraduate School, Monterey, California, April 19. Invited.
J.W.Chinneck and M. MacLeod (2006), "Effective Multistart for Reaching Feasibility in Difficult Nonlinear Programs", INFORMS, Pittsburgh, November 58.
J.W. Chinneck (2006), "Open Source Texts and Teaching Materials", INFORMS, Pittsburgh, November 58.
J.W. Chinneck (2006), "ActiveConstraint Variable Ordering for Faster Feasibility of Mixed Integer Linear Programs ", Workshop on Hybrid Methods and Branching Rules in Combinatorial Optimization, Centre de Recherches Mathématiques, Université de Montréal, Montréal, September 1822.
M. MacLeod and J.W. Chinneck (2006), "Efficient Multistart for Reaching Feasibility in Difficult Nonlinear Programs", CORS/Optimization Days, May 810, Montreal, Canada.
J.W. Chinneck (2006), "Analyzing Infeasible Optimization Models", Department of Mathematics, University of Haifa, Jan. 10, Haifa, Israel. Invited.
J.W. Chinneck (2006), "Analyzing Infeasible Optimization Models", School of Computational Engineering and Science, McMaster University, Feb. 13, Hamilton, Canada. Invited.
J.W. Chinneck and W. Ibrahim (2005), "Improving Solver Success in Reaching Feasibility for Sets of Nonlinear Constraints", INFORMS, San Francisco, November 1216, and CORS, Halifax, May 1618.
D. Wojtaszek and J.W. Chinneck (2005), "Faster MIP Solutions by Early Estimates of the Optimal Objective Function Value", Optimization Days, Montreal, May 911.
J.W. Chinneck and W. Ibrahim (2005), "Improving Solver Success in Reaching Feasibility for Sets of Nonlinear Constraints", ICS 2005, Annapolis, USA, January 57.
J.W. Chinneck, M. Nakhla, and Q.J. Zhang (2004), "ComputerAided Design for Electrical and Computer Engineering", INFORMS 2004, Denver, Colorado, October 2427. Invited tutorial.
J.W. Chinneck(2004), "Infeasibility and Optimization", CIST04 Conference, Denver, Colorado, October 2326.
J.W. Chinneck (2004), "MProbe Analysis of Nonlinear Function Shape in NEOS", INFORMS 2004, Denver, Colorado, October 2427.
J.W. Chinneck and A. Moghrabi (2004), "Constructing Better Decision Trees for Classification", INFORMS 2004, Denver, Colorado, October 2427.
J.W. Chinneck (2004), "Analyzing Infeasible Optimization Models", CORS/INFORMS Joint International Meeting, Banff, Canada, May 1619. Invited tutorial (pdf).
J.W. Chinneck and Jagat Patel (2003), "Faster MIP Solutions Through Better Variable Ordering", ISMP2003, Copenhagen, August 1722.
John W. Chinneck, Suryani Chao, and Rafik Goubran (2003), "Assigning Tasks inVoiceoverIP Gateway Multiprocessors", CORS Conference, Vancouver, June14.
J.W. Chinneck and J. Patel (2002), "Faster MIP Solutions through Better Variable Ordering", INFORMS, San Jose, November 1720.
J.W. Chinneck (2002), "The Constraint Consensus Method for Tightening Variable Bounds in Nonlinear Programs", MOPTA ’02, McMaster University, Hamilton, Canada, August 13.
J.W. Chinneck (2002), "Developments in MProbe: Approximating the Feasible Region", APMOD 2002, Varenna, Italy, June 1619.
J.W. Chinneck and J. Patel (2002), "Faster MIP Solutions Through Better Variable Ordering", CORS, Toronto, Canada, May 25.
A. Moghrabi, and J.W. Chinneck (2001), "Adaptive Classification Decision Trees", INFORMS, Miami, November 47.
J.W. Chinneck (2001), "Fast Algorithms for the Maximum Feasibility Problem", INFORMS, Miami, November 47.
J.W. Chinneck (2001), "Discovering the Characteristics of Mathematical Programs via Sampling", MOPTA01, Hamilton, August 24.
J.W. Chinneck (2000), "MProbe: Software for Analyzing Mathematical Programs",INFORMS, San Antonio, November 58.
J.W. Chinneck (2000), "Analyzing Mathematical Programs via Sampling", ISMP2000, Atlanta, August 711.
J.W. Chinneck (2000), "PreSolution Analysis of Complex Mathematical Programs via Sampling", Applied Mathematical Programming and Modeling (APMOD2000), London, England, April 1719.
J.W. Chinneck (2000), "MProbe: What's in your Mathematical Program?", INFORMS, Salt Lake City, May 710.
J.W. Chinneck (2000), "Discovering the Characteristics of Mathematical Programs via Sampling", CORS, Edmonton, May 2931.
J.W. Chinneck (1999), "Modeling Support for Constraint Programming", INFORMS, Philadelphia, November 710.
J.W. Chinneck and H. Li (1999), "A Generic Graphical Interface for Network Modeling", INFORMS, Philadelphia, November 710.
J.W. Chinneck (1999), "MProbe: Software for Analyzing Mathematical Programs", CORS Conference, Windsor, June 79.
J.W. Chinneck (1999), "MProbe: Software for Analyzing Mathematicl Programs", Optimization Days, Montreal, May 1012.
J.W. Chinneck (1999), "Classification Using Linear Programming Infeasibility Analysis", INFORMS, Cincinnati, May 25.
J.W. Chinneck (1999), "MProbe: Analyzing a Mathematical Program", INFORMS, Cincinnati, May 25.
J.W. Chinneck (1998), "Nonlinear Programming for the Rest of Us", INFORMS, Seattle, October 2528.
J.W. Chinneck (1998), "Multicategory Classification via LP Infeasibility Analysis", INFORMS, Seattle, October 2528.
J.W. Chinneck (1998), "Estimating the Shape of Nonlinear Functions and Regions", CORS/INFORMS, Montreal April 2629.
J.W. Chinneck (1998), "Analyzing Infeasible Mathematical Programs", INFORMS CSTS, Monterey, January 79.
J.W. Chinneck (1997), "Computer Tools for Analyzing Infeasible Mathematical Programs", ISMP'97, Lausanne, August 2429.
J.W. Chinneck (1997), "New IMPS Software: A Requirements Analysis", ISMP'97, Lausanne, August 2429.
J.W. Chinneck (1997), "MProbe: Software for Exploring Nonlinear Models", CORS'97, Ottawa, May 2628. Also presented at Optimization Days 1997, Montreal, May 1214.
M. Lavoie and J.W. Chinneck (1997), "SLA Optimizer: Optimization by Sequential LargeScale Approximation", CORS'97, Ottawa May 2628. Also presented at Optimization Days 1997, Montreal, May 1214.
R. Awad and J.W. Chinneck (1997), "Proctor Scheduling at Carleton University", CORS'97, Ottawa, May 2628 (invited).
J.W. Chinneck (1997), "MProbe: Estimating the 'Shape' of Nonlinear Functions", INFORMS, San Diego, May 47.
J.W. Chinneck (1996) "Help! Computer Tools Can Assist When Your Mathematical Program is Infeasible or Otherwise Broken", Optimization Days, 1996, Montreal, May 1315.
J.W. Chinneck (1995), "Tools for the PreSolution Analysis of Nonlinear Programs", CORS Conference, Calgary, May 2325.
J.W. Chinneck (1995), "An Effective Heuristic for the IIS SetCovering Approach to Analyzing Infeasible LPs", Optimization Days 1995, Montreal, May 1012.
J.W. Chinneck (1995), "A Toolkit for Presolution Analysis of Nonlinear Programs", INFORMS Conference, Los Angeles, April 2326.
J.W. Chinneck (1995), "A Toolkit for Presolution Analysis of Nonlinear Programs", INFORMS Conference, Los Angeles, April 2326.
J.W. Chinneck (1994), "An Introduction to Processing Networks", CORS/Optimization Days, Montreal, May, 30  June 1.
M. Lavoie and J.W. Chinneck (1994), "PROFLOW: Formulating, Analyzing, and Solving Processing Networks", CORS/Optimization Days, Montreal, May 30  June 1.
R.H.H. Moll, and J.W. Chinneck (1994), "Processing Network Models for Forest Management", CORS/Optimization Days, Montreal, May 30  June 1.
J.W. Chinneck, (1994), "Computer Codes for the Analysis of Infeasible LPs",TIMS/ORSA Conference, Boston, April 24  26.
V. Pureza, J.W. Chinneck and G.M. Karam (1993), "CLPF: Uma Heuristica para Aloca?ao de Tarefas em Ambiente de Multiprocessadores de Sinal Digital", Conference of the Operations Research Society of Brazil.
J.W. Chinneck, (1993), Analyzing Infeasible Mathematical Programs", Optimization Days 1993, Montreal May 1214.
M.W. Carter, G. Laporte and J.W. Chinneck, (1993), "An Introduction to EXAMINE: A Flexible Examination Scheduling System", AACRAO Conference, Orlando, April 1721.
J.W. Chinneck, (1993), "Finding Minimal Infeasible Sets of Constraints in Infeasible Mathematical Programs", APMOD93 Symposium on Applied Mathematical Programming and Modelling, Budapest, January 68 (invited).
M.W. Carter, G. Laporte and J.W. Chinneck, (1992), "A General Examination Scheduling System", Optimization Days, Montreal, May 46.
J.W. Chinneck, (1992), "Debugging Infeasible Instances of Linear and Nonlinear Programs", TIMS/ORSA Conference, San Francisco, November, (invited).
J.W. Chinneck, (1992), "Analyzing Infeasible Nonlinear Programs", TIMS/ORSA Conference, Orlando, April.
J.W. Chinneck, (1991), "Focusing the Diagnosis of Infeasible LPs", TIMS/ORSA Conference, Nashville, May 1215.
J.W. Chinneck, (1990), "Localizing and Analyzing Formulation Errors in Networks", CORS Conference, Ottawa, May 2224.
J.W. Chinneck (1989), "A Program for Identifying Formulation Errors in Processing Network Models", CORS/TIMS/ORSA Conference, Vancouver, May 8 10.
E.W. Dravnieks and J.W. Chinneck (1989), "Identification of Constraint Sets Causing Infeasibility in LPs", CORS/TIMS/ORSA Conference, Vancouver, May 810.
J.W. Chinneck (1988), "Detecting Pathological Structures in Processing Networks", TIMSORSA Conference, Washington, D.C., April 2527.
J.W. Chinneck (1987), "Building Processing Networks", ORSATIMS Conference, St. Louis, October 2528.
S.C. Boyd and J.W. Chinneck, (1987), "The Feasibility Problem for Processing Networks", 18th Southeastern International Conference on Combinatorics, Graph Theory, Computing, Florida Atlantic University, Boca Raton, February 2327.
J.W. Chinneck and M. Chandrashekar, (1978), "Assessment of Alternatives in Community Energy Planning", First International Conference on Energy and Community Development, Athens, July 1015.
J.W. Chinneck, (1983) "SystemTheoretic Overview Models of Industrial Plant Energy Systems Incorporating Exergy", Ph.D. Thesis, Systems Design, University of Waterloo.
J.W. Chinneck, (1978), "Models for Analysis of Energy Systems", M.A.Sc. Thesis, Systems Design, University of Waterloo.
J.W. Chinneck and H.J. Greenberg (1999), "Intelligent Mathematical Programming Software: Past Present, and Future", Newsletter of the INFORMS Computing Society, Vol. 20, no. 1. Pdf source.
J.W. Chinneck, (1992), "Advent of the Operations Analyst", article, OR/MS Today, October.
J.W. Chinneck and G.M. Karam, (1991), Book Review of "Constraint Satisfaction in Logic Programming" by Pascal van Hentenryck, ORSA Journal on Computing, Vol. 3, No. 1, pp. 8283.
Last update: June 14, 2017.
Back to the Systems and Computer Engineering Page
Questions and comments regarding this site? webweavers@sce.carleton.ca