Title: Clustering-based heuristic for the workload balancing problem in enterprise logistics

Authors: S.P. Anbuudayasankar, K. Ganesh, S.C. Lenny Koh, K. Mohandas

Addresses: Department of Mechanical Engineering, Amrita School of Engineering, Amrita University, Ettimadai, Coimbatore – 641105, India. ' Manufacturing Industry Solutions Unit, Tata Consultancy Services Limited, Vikhroli, Mumbai – 400079, India. ' Logistics and Supply Chain Management Research Group, Management School, University of Sheffield, Sheffield S10 2TN, UK. ' Department of Mechanical Engineering, Amrita School of Engineering, Amrita University, Ettimadai, Coimbatore – 641105, India

Abstract: Workload balancing between drivers in transshipment of goods is a critical humanitarian issue in enterprise logistics management. This problem is modelled as a multiple Travelling Salesman Problem with Workload Balancing (mTWB). The problem is addressed under the condition that the load for all the drivers must be balanced on a trip. We propose a clustering-based heuristic to solve the mTWB with the objective of balancing the workload amongst drivers. The methodology is tested over a range of benchmark data sets and is found to give satisfactory results with high convergence in reasonable time.

Keywords: enterprise logistics; multiple travelling salesman problem; workload balancing; mTWB; clustering based heuristics; logistics management; modelling; driver workload.

DOI: 10.1504/IJVCM.2009.028605

International Journal of Value Chain Management, 2009 Vol.3 No.3, pp.302 - 315

Published online: 20 Sep 2009 *

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