Title: Comparison of fuzzy C-mean clustering and 0-1 integer programming model for employee routing problem

Authors: R.A. Malairajan; K. Ganesh; K. Nallasivam; M. Punniyamoorthy

Addresses: Department of Mechanical Engineering, Anna University of Technology Tirunelveli, Tuticorin Campus, Tuticorin 628008, India ' Supply Chain Management – Center of Competence, McKinsey Knowledge Center, McKinsey and Company, 8th Floor, DLF Plaza Tower, DLF City Phase 1, Gurgaon 122 002, Haryana, India ' Department of Management Studies, National Institute of Technology, Tiruchirappalli – 620015, Tamilnadu, India ' Department of Management Studies, National Institute of Technology, Tiruchirappalli – 620015, Tamilnadu, India

Abstract: In a real time life, vehicle routing problems (VRP) arises whenever a set of vehicles is available to serve a set of transportation requests. The work carried in this paper focuses on understanding the concept of VRP and applying the techniques to a real time problem, which relates to the picking up of employees of an organisation by a fleet of buses. The problem is modelled as a employee routing problem (ERP), i.e., each bus has a limited number of seats and the number of employees picked up by each bus should be less than or equal to the maximum capacity of the bus. The techniques used here are fuzzy C-mean clustering and 0-1 integer programming model for obtaining the allocation of employees to each bus. The other techniques include nearest neighbourhood, which is used to obtain the initial route for the buses and 2-opt method, which is used to improve the travelling route by reducing the total cost and thus it helps in achieving the objective of ERP.

Keywords: supply chain management; SCM; vehicle routing problem; VRP; fuzzy C-means; integer programming; employee routing; employee transport; employee allocation; buses; bus routes; nearest neighbourhood; 2-opt method.

DOI: 10.1504/IJVCM.2012.052434

International Journal of Value Chain Management, 2012 Vol.6 No.4, pp.303 - 330

Published online: 16 Aug 2014 *

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