In many situations, a set of hard constraints encodes the feasible configurations of some system or product over which users have preferences. We consider the problem of computing a best feasible solution when the use...
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ISBN:
(纸本)3540202021
In many situations, a set of hard constraints encodes the feasible configurations of some system or product over which users have preferences. We consider the problem of computing a best feasible solution when the user's utilities are partially known. Assuming bounds on utilities, efficient mixed integer linear programs are devised to compute the solution with minimax regret while exploiting generalized additive structure in a user's utility function.
Since the early 909;s that constraint Logic programming (CLP) has been used to solve Combinatorial Search Problems. Generally, CLP has a good performance with highly constrained problems, but it lacks a "globa...
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ISBN:
(纸本)3540202021
Since the early 90's that constraint Logic programming (CLP) has been used to solve Combinatorial Search Problems. Generally, CLP has a good performance with highly constrained problems, but it lacks a "global perspective" of the search space, making the search for the optimal solution more difficult when the problems becomes larger and less constrained. On the other hand, Local Search Methods explore the search space directly through an "intelligent" construction of solution neighbourhoods, turning these methods suitable for solving less constrained and large search spaces problems. the aim of this paper is to present a hybridisation framework that allows combining Local Search methods withconstraint Logic programming. the first results demonstrate that while maintaining the CLP strengths it is possible to overcome their weaknesses and improve its search efficiency.
We show an algorithm for bound consistency of global cardinality constraints, which runs in time O(n+n9;) plus the time required to sort the assignment variables by range endpoints, where n is the number of assignm...
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ISBN:
(纸本)3540202021
We show an algorithm for bound consistency of global cardinality constraints, which runs in time O(n+n') plus the time required to sort the assignment variables by range endpoints, where n is the number of assignment variables and n' is the number of values in the union of their ranges. We thus offer a fast alternative to Regin's arc consistency algorithm [6] which runs in time O(n(3/2) n') and space O(n . n'). Our algorithm can also narrow the bounds for the number of occurrences of each value, which has not been done before.
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