Title: CLING: heuristic to solve integrated resource allocation and routing problem with time window

Authors: R.A. Malairajan; K. Ganesh; Matti Muhos; Päivi Iskanius

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. ' Oulu Southern Institute, University of Oulu, Pajatie 5, FI-85500 Nivala, Finland. ' Northern Research and Innovation Platform, Thule Institute, University of Oulu, P.O. Box 7300, 90014, Finland

Abstract: One of the important extensions of the classical resource allocation problem is integrated resource allocation and routing problem with time window (IRARPTW). IRARPTW problem focuses on the time window for the service at the demanding node with the consideration of travel time of vehicle for a varying demand-oriented multi-echelon supply chain with the consideration of limitation on the number of supply catalyst resource. We have developed a unified heuristic named clustering inherent genetic algorithm (CLING) to solve vehicle routing problem with time windows and IRARPTW. Heuristic CLING was tested for benchmark datasets of VRPTW and derived datasets of IRARPTW and yielded encouraging results.

Keywords: resource allocation; time windows; vehicle routing problem; clustering; genetic algorithms; CLING; IRARPTW; multi-echelon supply chains; vehicle travel time.

DOI: 10.1504/IJSOM.2012.048832

International Journal of Services and Operations Management, 2012 Vol.13 No.2, pp.247 - 266

Published online: 23 Aug 2014 *

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