Nature-Inspired Techniques for Dynamic Constraint Satisfaction Problems

نویسندگان

چکیده

Combinatorial applications such as configuration, transportation and resource allocation often operate under highly dynamic unpredictable environments. In this regard, one of the main challenges is to maintain a consistent solution anytime constraints are (dynamically) added. While many solvers have been developed tackle these applications, they work idealized assumptions environmental stability. order address limitation, we propose methodology, relying on nature-inspired techniques, for solving constraint problems when added dynamically. The choice techniques motivated by fact that iterative algorithms, capable maintaining set promising solutions, at each iteration. Our methodology takes advantage two properties, follows. We first solve initial problem save final state (and related population) after obtaining solution. This saved context will then be used resume point finding, in an incremental manner, new solutions subsequent variants problem, More precisely, once found, from current search (if old no longer feasible), can seen optimization where look feasible satisfying constraints, while minimizing differences with previous sequence. latter objective ensures find least disruptive solution, very important including scheduling, planning timetabling. Following our proposed variant several problems. Constraint represented using well-known satisfaction (CSP) paradigm. Dealing additions environment expressed series static CSPs, resulting change adding constraints. sequence CSPs called CSP (DCSP). To assess performance conducted experiments randomly generated DCSP instances, following RB model. results reported discussed.

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ژورنال

عنوان ژورنال: Operations Research Forum

سال: 2022

ISSN: ['2662-2556']

DOI: https://doi.org/10.1007/s43069-021-00116-6