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

R.A. Malairajan, K. Ganesh, Matti Muhos and Päivi Iskanius

International Journal of Services and Operations Management, 2012, vol. 13, issue 2, 247-266

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. (search for similar items in EconPapers)
Date: 2012
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