A Customized Bi-Objective Location-Routing Problem for Locating Post Offices and Delivery of Post Parcels

Authors

  • Kaveh Khalili-Damghani Department of Industrial Engineering Faculty of Industrial Engineering South Tehran Branch Islamic Azad University Tehran, Iran
  • Mohammad Tahmasebi Department of Industrial Engineering Faculty of Industrial Engineering South Tehran Branch Islamic Azad University Tehran, Iran
  • Vahid Ghezavati Department of Industrial Engineering Faculty of Industrial Engineering South Tehran Branch Islamic Azad University Tehran, Iran
Abstract:

One of the most important problems for distribution companies is to find the best locations for depots and to find proper routes for transportation vehicles and to optimize supply network. This study intends to develop a model for the problem of location-routing in post offices. So, a new Bi-Objective Location-Routing Problem for Locating Town Post Office and Routing Parcels is defined. This problem is modeled through mixed-integer mathematical programming. The aim of proposed model is to select potential post offices and to find optimal routes for transportation vehicles while time constraints are taken into account. The proposed model is applied in a real case study including eight main post area and 21 regional offices in Tehran, Iran. A goal programming approach is proposed to solve this bi-objective optimization model. The GAMS Software is used to code and solve the associated mathematical model. Some required parameters of the model such as demands are estimated using Geographical Information System (GIS) and simulation methods. The results of proposed model including the objective functions, decision variables, and proposed routing of vehicles have been compared with the existing practical solutions. Sensitivity analysis on main parameters of proposed models is accomplished and the results are analyzed. This comparison illustrate the efficacy and applicability of proposed approach.

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Journal title

volume 10  issue Issue 1

pages  1- 17

publication date 2017-04-10

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