Solving a Novel Model of Multi-Objective Location-Arc Routing Problem of Multi-Period with Time Window and Risk of Robby Valuable Product (Case Study: Treasury Bank)

Document Type : Scientific - Research

Authors
atefeh kahfi 1
seyedmohammad seyedhosseini 2
Reza Tavakkoli-Moghaddam 3
1 Department of Industrial Engineering, College of Engineering, University of Payame Noor, Tehran, Iran
2 Professor, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
3 Professor, School of Industrial Engineering, College of Engineering, University of Tehran
10.22119/jte.2018.77225
Abstract
A Location-Arc Routing Problem (LARP) is a practical problem, while a few mathematical programming models have been considered for this problem so far. To the best our knowledge, it is the first time that a mixed non-linear bi-objective programming model is proposed for a multi-period LARP with time window and risk of robby valuable product. In the proposed model, vehicles can meet the customer for delivery or receive product. 22 standard problems are solved with the ε-constraint method, MOPSO, MOBA, MODA and NSGA-II. The computational results are shown the efficiency of the MODA on indicators of multi-objective problems for solving them. The deviation of the MODA objectives with the ε-constraint at the extreme is equal to 1.32% and 0.45% average. The proposed model is used for solving the location problem of the treasury of a bank as a case study. The case study is a node routing problem with nearby nodes that has transform to arc routing. According to the rules, experts have selected 13 treasuries between 18 candidates, that the Pareto boundary provided by the MODA for the 10 case studies.
Keywords
Multi-objective location-arc routing problem, &epsilon
- constraints method, Cash-in-transit risk, Dragonfly algorithm
Subjects
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Quarterly Journal of Transportation Engineering
Volume 17, Issue 3 - Serial Number 68
Winter 2026
Pages 5455-5483

  • Receive Date 27 May 2018
  • Revise Date 09 October 2018
  • Accept Date 10 October 2018