• Title/Summary/Keyword: Probabilistic Traveling Salesman Problem

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A Minimum Expected Length Insertion Algorithm and Grouping Local Search for the Heterogeneous Probabilistic Traveling Salesman Problem (이종 확률적 외판원 문제를 위한 최소 평균거리 삽입 및 집단적 지역 탐색 알고리듬)

  • Kim, Seung-Mo;Choi, Ki-Seok
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.33 no.3
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    • pp.114-122
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    • 2010
  • The Probabilistic Traveling Salesman Problem (PTSP) is an important topic in the study of traveling salesman problem and stochastic routing problem. The goal of PTSP is to find a priori tour visiting all customers with a minimum expected length, which simply skips customers not requiring a visit in the tour. There are many existing researches for the homogeneous version of the problem, where all customers have an identical visiting probability. Otherwise, the researches for the heterogeneous version of the problem are insufficient and most of them have focused on search base algorithms. In this paper, we propose a simple construction algorithm to solve the heterogeneous PTSP. The Minimum Expected Length Insertion (MELI) algorithm is a construction algorithm and consists of processes to decide a sequence of visiting customers by inserting the one, with the minimum expected length between two customers already in the sequence. Compared with optimal solutions, the MELI algorithm generates better solutions when the average probability is low and the customers have different visiting probabilities. We also suggest a local search method which improves the initial solution generated by the MELI algorithm.

A hybrid tabu search algorithm for Task Allocation in Mobile Crowd-sensing

  • Akter, Shathee;Yoon, Seokhoon
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.4
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    • pp.102-108
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    • 2020
  • One of the key features of a mobile crowd-sensing (MCS) system is task allocation, which aims to recruit workers efficiently to carry out the tasks. Due to various constraints of the tasks (such as specific sensor requirement and a probabilistic guarantee of task completion) and workers heterogeneity, the task allocation become challenging. This assignment problem becomes more intractable because of the deadline of the tasks and a lot of possible task completion order or moving path of workers since a worker may perform multiple tasks and need to physically visit the tasks venues to complete the tasks. Therefore, in this paper, a hybrid search algorithm for task allocation called HST is proposed to address the problem, which employ a traveling salesman problem heuristic to find the task completion order. HST is developed based on the tabu search algorithm and exploits the premature convergence avoiding concepts from the genetic algorithm and simulated annealing. The experimental results verify that our proposed scheme outperforms the existing methods while satisfying given constraints.

Application of Ant System Algorithm on Parcels Delivery Service in Korea (국내택배시스템에 개미시스템 알고리즘의 적용가능성 검토)

  • Jo, Wan-Kyung;Rhee, Jong-Ho
    • Journal of Korean Society of Transportation
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    • v.23 no.4 s.82
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    • pp.81-91
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    • 2005
  • The Traveling Salesman Problem(TSP) is one of the NP-complete (None-deterministic Polynomial time complete) route optimization problems. Its calculation time increases very rapidly as the number of nodes does. Therefore, the near optimum solution has been searched by heuristic algorithms rather than the real optimum has. This paper reviews the Ant System Algorithm(ANS), an heuristic algorithm of TSP and its applicability in the parcel delivery service in Korea. ASA, which is an heuristic algorithm of NP-complete has been studied by M. Dorigo in the early 1990. ASA finds the optimum route by the probabilistic method based on the cumulated pheromone on the links by ants. ASA has been known as one of the efficient heuristic algorithms in terms of its calculation time and result. Its applications have been expanded to vehicle routing problems, network management and highway alignment planning. The precise criteria for vehicle routing has not been set up in the parcel delivery service of Korea. Vehicle routing has been determined by the vehicle deriver himself or herself. In this paper the applicability of ASA to the parcel delivery service has been reviewed. When the driver s vehicle routing is assumed to follow the Nearest Neighbor Algorithm (NNA) with 20 nodes (pick-up and drop-off places) in $10Km{\times}10Km$ service area, his or her decision was compared with ASA's one. Also, ASA showed better results than NNA as the number of nodes increases from 10 to 200. If ASA is applied, the transport cost savings could be expected in the parcel delivery service in Korea.