• 제목/요약/키워드: Traveling Salesman Problem With Time Windows (TSPTW)

검색결과 2건 처리시간 0.019초

시간제약이 있는 외판원 문제를 위한 메타휴리스틱 기법 (An Iterative Insertion Algorithm and a Hybrid Meta Heuristic for the Traveling Salesman Problem with Time Windows)

  • 김병인
    • 대한산업공학회지
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    • 제33권1호
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    • pp.86-98
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    • 2007
  • This paper presents a heuristic algorithm for the traveling salesman problem with time windows (TSPTW). Aniterative insertion algorithm as a constructive search heuristic and a hybrid meta heuristic combining simulatedannealing and tabu search with the randomized selection of 2-interchange and a simple move operator as animproving search heuristic are proposed, Computational tests performed on 400 benchmark problem instancesshow that the proposed algorithm generates optimal or near-optimal solutions in most cases. New best knownheuristic values for many benchmark problem sets were obtained using the proposed approach.

지연비용을 고려한 서비스 시간대가 존재하는 외판원 문제에 대한 발견적 해법 (A Heuristc Algorithm for the Traveling Salesman Problem with Time Windows and Lateness Costs)

  • 서병규;김종수
    • 대한산업공학회지
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    • 제27권1호
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    • pp.18-24
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    • 2001
  • This paper presents a model and a heuristic algorithm for the Traveling Salesman Problem with Time Windows(TSPTW). The main difference of our model compared with the previous ones lies in that the time windows we are concerned are more flexible and realistic than the previous ones. In the typical TSPTW, the service at a node must begin within the time grid called the time window that is defined by the earliest and the latest time to start the service at each node. But, in real business practice, a lateness cost is usually penalized rather than the service is prohibited at all when a vehicle arrives after the latest time. Considering this situation, we develop a model with a new time window that allows an arrival after the latest time and penalizes the late arrival by charging a lateness cost. A two-phased heuristic algorithm is proposed for the model and is extensively tested to verify the accuracy and efficiency of the algorithm.

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