constraintprogramming (CP) is a healthy research area in the academic community. the growing number of participants to the CP conference series, as well as the number of workshops around CP is a good evidence of it. ...
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(纸本)3540232419
constraintprogramming (CP) is a healthy research area in the academic community. the growing number of participants to the CP conference series, as well as the number of workshops around CP is a good evidence of it. Many major conferences have a CP track, both in artificial intelligence, and in operations research. the existence of several commercial companies that offer CP tools and services is a further evidence of the value of CP as an industrial technology. ILOG is one of such companies. One of our uniqueness, as far as CP is concerned, is that the research and development team that produces our CP products is also responsible for the development of our mathematical programming (MP) tool, namely ILOG CPLEX. this provides a unique opportunity to contrast the way these products are developed, marketed and used. In this paper we argue that current CP technology is much too complex to use for the average engineer. Worse, we believe that much of the research occurring in the CP academic community makes this even worse every year. the rest of the paper provides evidence for this claim, and suggests ways to address the issue of simplicity of use by looking at how a similar issue has been addressed in the mathematical programming community.
the Set Covering Machine (SCM) is a machine learning algorithm that constructs a conjunction of Boolean functions. this algorithm is motivated by the minimization of a theoretical bound. However, finding the optimal c...
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We combine mixed integer linear programming (MILP) and constraintprogramming (CP) to solve planning and scheduling problems. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked...
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It is well-known that variable ordering heuristics play a central role in solving efficiently constraint Satisfaction Problem (CSP) instances. From the early 809;s, and during more than two decades, the dynamic var...
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In this paper, we present a constraint-partitioning approach for finding local optimal solutions of large-scale mixed-integer nonlinear programming problems (MINLPs). Based on our observation that MINLPs in many engin...
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Solution counting and solution space integration over linear constraints are important problems with many applications. Previous works addressed either only counting integer points in polytopes (integer counting) with...
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the Stable Marriage problem (SM) is an extensively-studied combinatorial problem with many practical applications. In this paper we present two encodings of an instance I of SM as an instance J of a constraint Satisfa...
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constraint satisfaction problems (CSPs) sometimes contain both variable symmetries and value symmetries, causing adverse effects on CSP solvers based on tree search. As a remedy, symmetry breaking constraints are comm...
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constraint satisfaction problems (CSPs) sometimes contain both variable symmetries and value symmetries, causing adverse effects on CSP solvers based on tree search. As a remedy, symmetry breaking constraints are commonly used. While variable symmetry breaking constraints can be expressed easily and propagated efficiently using lexicographic ordering, value symmetry breaking constraints are often difficult to formulate. In this paper, we propose two methods of using symmetry breaking constraints to tackle value symmetries. First, we show theoretically when value symmetries in one CSP correspond to variable symmetries in another CSP of the same problem. We also show when variable symmetry breaking constraints in the two CSPs, combined using channeling constraints, are consistent. Such results allow us to tackle value symmetries efficiently using additional CSP variables and channeling constraints. Second, we introduce value precedence, a notion which can be used to break a common class of value symmetries, namely symmetries of indistinguishable values. While value precedence can be expressed using inefficient if-then constraints in existing CSP solvers, we propose efficient propagation algorithms for implementing global value precedence constraints. We also characterize several theoretical properties of the value precedence constraints. Extensive experiments are conducted to verify the feasibility and efficiency of the two proposals.
Recent improvements in constraintprogramming have made it possible to tackle hard problems in a practical way. Before this, these problems were solved only by specialized programs often complex to implement. Scheduli...
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the Compact-Table (CT) algorithm is the current state-of-the-art algorithm for enforcing Generalized Arc Consistency (GAC) on table constraints during search. Recently, algorithms for enforcing Pairwise Consistency (P...
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