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Multi-start Tabu Search Algorithm for Solving OVRPTW

Liming Wang

Open publisher page 2 citations

Abstract

On the basis of describing the Open Vehicle Routing Problem with Time Windows(OVRPTW),a Multi-Start Tabu Search(MS-TS) algorithm is presented.In this algorithm,the random initial solution is generated by the two-phase method of combining the sweep algorithm and push forward insertion heuristic,the neighborhood structure is constructed by a mixed heuristic algorithm,the capability of global optimization is improved by designing global and local Tabu list.With the normal test examples,the experiment is done,and a good optimization result is obtained.

About this research paper

What this paper is about

On the basis of describing the Open Vehicle Routing Problem with Time Windows(OVRPTW),a Multi-Start Tabu Search(MS-TS) algorithm is presented.In this algorithm,the random initial solution is generated by the two-phase method of combining the sweep algorithm and push forward insertion heuristic,the neighborhood structure is constructed by a mixed heuristic algorithm,the capability of global optimization is improved by designing global and local Tabu list.With the normal test examples,the experiment is done,and a good optimization result is obtained.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

On the basis of describing the Open Vehicle Routing Problem with Time Windows(OVRPTW),a Multi-Start Tabu Search(MS-TS) algorithm is presented.In this algorithm,the random initial solution is generated by the two-phase method of combining the sweep algorithm and push forward insertion heuristic,the neighborhood structure is constructed by a mixed heuristic algorithm,the capability of global optimization is improved by designing global and local Tabu list.With the normal test examples,the experiment is done,and a good optimization result is obtained.

Key concepts: Tabu search, Computer science, Guided Local Search, Algorithm, Heuristic, Vehicle routing problem, Mathematical optimization, Hill climbing

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