Variable neighborhood search for the inventory routing and scheduling problem in a supply chain

This article addresses a technician routing and scheduling problem inspired from an application for the repair of electronic transactions equipment. It consists of designing routes for staff to perform requests while considering certain constraints and resources. The objective is to minimize a linear combination of total weighted distance, overtime, and maximize the served requests. An efficient meta-heuristic algorithm based on variable neighborhood search with an adaptive memory and advanced diversity management method is proposed. Numerical results show that the meta-heuristic outperforms the best existing algorithm from the literature which is a Tabu Search.

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RETRACTED: An Efficient Metaheuristic Approach for the Multi-Period Technician Routing and Scheduling Problem

Engineering, Technology & Applied Science Research ◽

10.48084/etasr.3091 ◽

2019 ◽

Vol 9 (5) ◽

pp. 4718-4723

Author(s):

A. Khattara ◽

W. R. Cherif-Khettaf ◽

M. Mostefai

Keyword(s):

Information Technologies ◽

Variable Neighborhood Search ◽

Neighborhood Search ◽

Scheduling Problem ◽

Conference Paper ◽

Routing And Scheduling ◽

International Conference ◽

Control Decision

This article has been retracted at the request of the Editor-in-Chief and of co authors W. R. Cherif-Khettaf and M. Mostefai, as the article is largely based on work presented previously at an international conference by the same authors. The conference paper is: A. Khattara, W. R. Cherif-Khettaf and M. Mostefai, "Variable neighborhood search procedures for the multi-period technician routing and scheduling problem", 4th International Conference on Control, Decision and Information Technologies (CoDIT), Spain, April 5-7, 2017 and the corresponding author of this submission was unaware of the publication of this conference's proceedings at the time of submission and review/publication of this paper.

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A Memetic Algorithm for the Inventory Routing Problem

10.21203/rs.3.rs-848529/v1 ◽

2021 ◽

Author(s):

Mohame Salim Amri Sakhri ◽

Mounira Tlili ◽

Ouajdi Korbaa

Keyword(s):

Supply Chain ◽

Variable Neighborhood Search ◽

Memetic Algorithm ◽

Population Based ◽

Single Type ◽

Neighborhood Search ◽

Inventory Routing ◽

Routing Problem ◽

Inventory Routing Problem ◽

Single Vehicle

Abstract In this paper, we investigated an Inventory Routing Problem (IRP) with deterministic customer demand, in a two-tiered supply chain. The supply chain network consists of a supplier who uses a single vehicle with a given capacity to deliver a single type of product to many customers. We are interested in population-based algorithms to solve our problem. A Memetic Algorithm (MA) is developed based on Genetic Algorithm (GA) and Variable Neighborhood Search methods (VNS). The proposed metaheuristics are tested on small and large sizes referenced benchmarks. The results of MA are compared with those of classical GA and with the optimal solutions from the literature. The comparison showed the efficiency of the MA use and its ability to generate high quality solutions within a reasonable time.

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