Titlebook: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problem; 5th International Co Laurent Perron,M

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Selected Challenges from Distribution and Commerce in the Airline and Travel Industrys to sell) to customers (business travelers & tourists). Such sales can be done directly or through a travel agent, both offline (during a discussion with an agent) or online (through a web site). Distribution for the travel industry has gone through impressive changes in the past decades with the a

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Constraint Integer Programming: A New Approach to Integrate CP and MIPg (MIP) methodologies. CIP is a generalization of MIP that supports the notion of general constraints as in CP. This approach is supported by the CIP framework SCIP, which also integrates techniques from SAT solving. SCIP is available in source code and free for non-commercial use..We demonstrate th

TERRA

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Multi-stage Benders Decomposition for Optimizing Multicore Architecturesll-known multicore platform, namely the Cell BE processor, and we address the problem of allocating and scheduling its processors, communication channels and memories, with the goal of minimizing application execution time..We have developed a complete optimization strategy based on Benders’ decompo

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Gap Reduction Techniques for Online Stochastic Project Schedulingems, and scheduling. For such applications which typically feature purely exogenous uncertainty, the one-step anticipatory algorithm was shown theoretically to be close to optimal when the stochasticity of the problem, measured by the anticipatory gap, is small. This paper studies the behavior of on

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Integrating Symmetry, Dominance, and Bound-and-Bound in a Multiple Knapsack Solvern, a bin-oriented, branch-and-bound algorithm. In this paper, we propose path-symmetry and path-dominance, which are instances of the symmetry detection by dominance detection approach for pruning symmetric nodes in the MKP branch-and-bound search space. In addition, we integrate the “bound-and-boun

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Cost Propagation – Numerical Propagation for Optimization Problemsion combines ideas from both constraint programming and integer programming into a single approach, where problems are iteratively solved by numerical propagation, with updates for single constraint terms in the component model..We outline a theory of propagation in terms of equivalent problems with

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Fitness-Distance Correlation and Solution-Guided Multi-point Constructive Search for CSPstructive search techniques on a number of constraint optimization and constraint satisfaction problems. In this paper, we perform a case study of the application of SGMPCS to a constraint satisfaction model of the multi-dimensional knapsack problem. We show that SGMPCS performs poorly. We then devel