A study of greedy, local search, and ant colony optimization approaches for car sequencing problems
作者： Jens Gottlieb , Markus Puchta , Christine Solnon
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摘要: This paper describes and compares several heuristic approaches for the car sequencing problem. We first study greedy heuristics, show that dynamic ones clearly outperform their static counterparts. then describe local search ant colony optimization (ACO) approaches, both integrate experimentally compare them on benchmark instances. ACO yields best solution quality smaller time limits, it is comparable to larger limits. Our algorithms proved one instance being feasible, which was formerly unknown whether satisfiable or not.
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