Title: REFING: heuristic to solve bi-objective resource allocation problem with bound and varying capacity

Authors: R.A. Malairajan; K. Ganesh; Tzong-Ru Lee; S.P. Anbuudayasankar

Addresses: Department of Mechanical Engineering, Anna University of Technology Tirunelveli, Tuticorin Campus, Tuticorin – 628008, India ' Supply Chain Management – Center of Competence, McKinsey Knowledge Center India Private Limited, McKinsey & Company, 8th Floor, DLF City Phase 1, DLF Plaza Tower, Gurgaon – 122002, Haryana, India ' Department of Marketing, National Chung Hsing University, Taichung 402, Taiwan ' Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amrita Nagar, Coimbatore – 641112, Tamilnadu, India

Abstract: One of the important extensions of the classical multi-commodity network flow (MCNF) problem in bi-objective resource allocation problem with bound and varying capacity (BORAPBVC). We developed a recursive function inherent genetic algorithm (REFING) to solve MCNF problem and BORAPBVC. The objective of BORAPBVC problem is to find the optimal allocation with the consideration of two objectives and lower and upper bound as the service limit in the serving nodes with varying capacity. The REFING heuristic is tested for randomly generated datasets of BORAPBVC. When compared with the results of brute force method, REFING has performed better both in terms of solution quality and computational time.

Keywords: multi-commodity network flow; bi-objective resource allocation; genetic algorithms; capacity variation; recursive function.

DOI: 10.1504/IJOR.2013.053620

International Journal of Operational Research, 2013 Vol.17 No.2, pp.145 - 169

Published online: 29 Jul 2014 *

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