000			01771naa a2200181 4500
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100			_aBasu, Sumanta
245			_aNeighborhood Reduction Strategy for Tabu Search Implementation in Asymmetric Traveling Salesman Problem
260			_a _b _c
300			_a49(4) Oct- Dec 2012, 400-412p.
520			_aThe Traveling Salesman Problem (TSP) is one of the most widely discussed problems in combinatorial optimization. It has many practical applications in fields of distribution and logistics management, scheduling problems etc. Since these problems are hard, in addition to exact algorithms, research has focused on heuristic techniques to solve TSPs. Computational time is a major concern while solving large TSPs. This problem intensifies further if the graph becomes asymmetric (ATSP). Metaheuristics like tabu search are widely used to find a reasonably good tour fast. Given the practical relevance of ATSPs the lack of literature on it is surprising. The primary objective of our work is to implement tabu search for large ATSPs to obtain good tours in reasonable time. To do that, we make the underlying graph sparse by developing an elite tour based preprocessing scheme. Tabu search is implemented on this reduced graph which results in a reduction of computational time. We also create diversified initial tours suitable for multi-start tabu search in this process. We present our computational experiences both on randomly generated instances and benchmark instances.
650			_aTabu Search
650			_aAsymmetric travelling salesman problem
650			_aPreprocessing Scheme
773	0		_d _oB-2508 _tBV- Opsearch (Jan - Dec 2012)
906			_aGeneral Management
942			_2ddc _c8
999			_c90397 _d90397