Capacitated location-routing problem with time windows under uncertainty

Mohammad Hossein Fazel Zarandi; Ahmad Hemmati; Soheil Davari; Burhan Turksen

doi:10.1016/j.knosys.2012.09.007

Capacitated location-routing problem with time windows under uncertainty

Mohammad Hossein Fazel Zarandi, Ahmad Hemmati, Soheil Davari, Burhan Turksen

Research output: Contribution to journal › Article › peer-review

92 Citations (SciVal)

Abstract

This paper puts forward a location-routing problem with time windows (LRPTW) under uncertainty. It has been assumed that demands of customers and travel times are fuzzy variables. A fuzzy chance constrained programming (CCP) model has been designed using credibility theory and a simulation-embedded simulated annealing (SA) algorithm is presented in order to solve the problem. To initialize solutions of SA, a heuristic method based on fuzzy c-means (FCM) clustering with Mahalanobis distance and sweep method have been employed. The numerical experiments clearly attest that the proposed solution approach is both effective and robust in solving problems with up to 100 demand nodes in reasonable times.

Original language	Undefined/Unknown
Pages (from-to)	480-489
Number of pages	10
Journal	Knowledge-Based Systems
Volume	37
DOIs	https://doi.org/10.1016/j.knosys.2012.09.007
Publication status	Published - 2013

Bibliographical note

cited By 57

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10.1016/j.knosys.2012.09.007

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Cite this

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title = "Capacitated location-routing problem with time windows under uncertainty",

abstract = "This paper puts forward a location-routing problem with time windows (LRPTW) under uncertainty. It has been assumed that demands of customers and travel times are fuzzy variables. A fuzzy chance constrained programming (CCP) model has been designed using credibility theory and a simulation-embedded simulated annealing (SA) algorithm is presented in order to solve the problem. To initialize solutions of SA, a heuristic method based on fuzzy c-means (FCM) clustering with Mahalanobis distance and sweep method have been employed. The numerical experiments clearly attest that the proposed solution approach is both effective and robust in solving problems with up to 100 demand nodes in reasonable times. ",

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AU - Fazel Zarandi, Mohammad Hossein

AU - Hemmati, Ahmad

AU - Davari, Soheil

AU - Turksen, Burhan

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AB - This paper puts forward a location-routing problem with time windows (LRPTW) under uncertainty. It has been assumed that demands of customers and travel times are fuzzy variables. A fuzzy chance constrained programming (CCP) model has been designed using credibility theory and a simulation-embedded simulated annealing (SA) algorithm is presented in order to solve the problem. To initialize solutions of SA, a heuristic method based on fuzzy c-means (FCM) clustering with Mahalanobis distance and sweep method have been employed. The numerical experiments clearly attest that the proposed solution approach is both effective and robust in solving problems with up to 100 demand nodes in reasonable times.

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