Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems: 7th International Conference, CPAIOR 2010 Bolog

ISBN-13: 9783642135194 / Angielski / Miękka / 2010 / 369 str.

Andrea Lodi; Michela Milano; Paolo Toth

Opis

The 7th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2010) was held in Bologna, Italy, June 16-18, 2010. The conference is intended primarily as a forum to focus on the integration and hybridization of the approaches of constraint programming (CP), arti?cial intelligence (AI), and operations research (OR) technologies for solving lar- scale and complex real-life combinatorial optimization problems. CPAIOR is focused on both theoretical and practical, application-oriented contributions. The interest of the researchcommunity in this conference is witnessed by the highnumber ofhigh-qualitysubmissions receivedthis year, reaching39 long and 33 short papers. From these submissions, we chose 18 long and 17 short papers to be published in full in the proceedings. ThisvolumeincludesextendedabstractsoftheinvitedtalksgivenatCPAIOR. Namely, one by Matteo Fischetti (University of Padova) on cutting planes and their use within search methods; another by Carla Gomes (Cornell University) on the recently funded NSF Expedition in Computing grant on the topic of computationalsustainabilityandonthepotentialapplicationofhybridoptimi- tion approachesto this area;a third by Peter Stuckey (University of Melbourne) on the integration of SATis?ability solvers within constraint programming and integer programming solvers."

Spis treści

Towards a MIP-Cut Metascheme.- Challenges for CPAIOR in Computational Sustainability.- Lazy Clause Generation: Combining the Power of SAT and CP (and MIP?) Solving.- On Matrices, Automata, and Double Counting.- The Increasing Nvalue Constraint.- Improving the Held and Karp Approach with Constraint Programming.- Characterization and Automation of Matching-Based Neighborhoods.- Rapid Learning for Binary Programs.- Hybrid Methods for the Multileaf Collimator Sequencing Problem.- Automatically Exploiting Subproblem Equivalence in Constraint Programming.- Single-Facility Scheduling over Long Time Horizons by Logic-Based Benders Decomposition.- Integrated Maintenance Scheduling for Semiconductor Manufacturing.- A Constraint Programming Approach for the Service Consolidation Problem.- Solving Connected Subgraph Problems in Wildlife Conservation.- Consistency Check for the Bin Packing Constraint Revisited.- A Relax-and-Cut Framework for Gomory’s Mixed-Integer Cuts.- An In-Out Approach to Disjunctive Optimization.- A SAT Encoding for Multi-dimensional Packing Problems.- Job Shop Scheduling with Setup Times and Maximal Time-Lags: A Simple Constraint Programming Approach.- On the Design of the Next Generation Access Networks.- Vehicle Routing for Food Rescue Programs: A Comparison of Different Approaches.- Constraint Programming and Combinatorial Optimisation in Numberjack.- Automated Configuration of Mixed Integer Programming Solvers.- Upper Bounds on the Number of Solutions of Binary Integer Programs.- Matrix Interdiction Problem.- Strong Combination of Ant Colony Optimization with Constraint Programming Optimization.- Service-Oriented Volunteer Computing for Massively Parallel Constraint Solving Using Portfolios.- Constraint Programming with Arbitrarily Large Integer Variables.- Constraint-Based Local Search for Constrained Optimum Paths Problems.- Stochastic Constraint Programming by Neuroevolution with Filtering.- The Weighted Spanning Tree Constraint Revisited.- Constraint Reasoning with Uncertain Data Using CDF-Intervals.- Revisiting the Soft Global Cardinality Constraint.- A Constraint Integer Programming Approach for Resource-Constrained Project Scheduling.- Strategic Planning for Disaster Recovery with Stochastic Last Mile Distribution.- Massively Parallel Constraint Programming for Supercomputers: Challenges and Initial Results.- Boosting Set Constraint Propagation for Network Design.- More Robust Counting-Based Search Heuristics with Alldifferent Constraints.