Combining ant colony optimization algorithm and dynamic programming technique for solving the covering salesman problem

Salari, Majid; Reihaneh, Mohammad; Sabbagh, Mohammad S.

doi:10.1016/j.cie.2015.02.019

Cited by 44 publications

(21 citation statements)

References 16 publications

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“…Laporte and Semet [ 19 ] proposed a CTP in which the nodes were classified into three groups: nodes that must be visited, nodes that must be covered, and nodes that can be covered or visited. Furthermore, Golden et al [ 20 ], Salari et al [ 21 ] and Salari et al [ 22 ] proposed local search algorithm, integer programing-based local search, and hybrid ant colony optimization to solve the CSP, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

A variable neighborhood search for the last-mile delivery problem during major infectious disease outbreak

et al. 2021

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Section: Literature Reviewmentioning

confidence: 99%

A variable neighborhood search for the last-mile delivery problem during major infectious disease outbreak

et al. 2021

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“…A generalization of the CSP is studied in [5] and [6] where an additional cost is incurred for every node visited by the tour and each node is associated with a weighted demand representing the minimum number of times it has to be covered. Another generalization of the CSP, called the generalized covering traveling salesman problem (GCTSP), is presented in [7].…”

Section: Related Literaturementioning

confidence: 99%

Time constrained maximal covering salesman problem with weighted demands and partial coverage

Özbaygın

Yaman

Karaşan

2016

Computers & Operations Research

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In a routing framework, it may not be viable to visit every single customer separately due to resource limitations or efficiency concerns. In such cases, utilizing the notion of coverage; i.e., satisfying the demand of multiple customers by visiting a single customer location, may be advantageous. With this motivation, we study the time constrained maximal covering salesman problem (TCMCSP) in which the aim is to find a tour visiting a subset of customers so that the amount of demand covered within a limited time is maximized. We provide flow and cut formulations and derive valid inequalities. Since the connectivity constraints and the proposed valid inequalities are exponential in the size of the problem, we devise different branch-and-cut schemes. Computational experiments performed on a set of problem instances demonstrate the effectiveness of the proposed valid inequalities in terms of strengthening the linear relaxation bounds as well as speeding up the solution procedure. Moreover, the results indicate the superiority of using a branch-and-cut methodology over a flow-based formulation. Finally, we discuss the relation between the problem parameters and the structure of optimal solutions based on the results of our experiments.

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“…Similarly, another example provided by Current and Schilling [6] is the construction of routes for visiting health care teams in developing countries, where medical services can only be delivered to a subset of villages but all users must be able to reach a visiting medical team. Different exact or metaheuristic approaches have been developed over the years for the CTP or small variants of this problem (2,6,10,14,16,19,21).…”

Section: Introductionmentioning

confidence: 99%

The stochastic close-enough arc routing problem

2017

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The Stochastic Close-Enough Arc Routing Problem is a challenging problem where utility companies seek for a minimum-cost tour in order to collect meter consumption remotely. The stochasticity lies in the uncertainty of collecting data due to failed transmissions. In this article, we propose a mathematical formulation for this problem. We introduce some preprocessing properties, develop an exact method and several heuristics. Computational results from experiments are presented and analyzed.

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Combining ant colony optimization algorithm and dynamic programming technique for solving the covering salesman problem

Cited by 44 publications

References 16 publications

A variable neighborhood search for the last-mile delivery problem during major infectious disease outbreak

A variable neighborhood search for the last-mile delivery problem during major infectious disease outbreak

Time constrained maximal covering salesman problem with weighted demands and partial coverage

The stochastic close-enough arc routing problem

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