Authors: Iman Kazemian; Samin Aref
Addresses: Department of Industrial Engineering, College of Engineering, University of Tehran, North Kargar, Tehran, P.O. Box 4563-11155, Iran ' Department of Computer Science, University of Auckland, Auckland, Private Bag 92019, New Zealand; Computer Science Practice Pathway Group, Unitec Institute of Technology, Auckland, Private Bag 92025, New Zealand
Abstract: This study presents a novel approach to the vehicle routing problem by focusing on greenhouse gas emissions and fuel consumption aiming to mitigate adverse environmental effects of transportation. A time-dependent model with time windows is developed to incorporate speed and schedule in transportation. The model considers speed limits for different times of the day in a realistic delivery context. Due to the complexity of solving the model, a simulated annealing algorithm is proposed to find solutions with high quality in a timely manner. Our method can be used in practice to lower fuel consumption and greenhouse gas emissions while total route cost is also controlled to some extent. The capability of method is depicted by numerical examples productively solved within 3.5% to the exact optimal for small and mid-sized problems. Moreover, comparatively appropriate solutions are obtained for large problems in averagely one tenth of the exact method restricted computation time.
Keywords: vehicle routing; green; time-dependent; time windows; greenhouse gas emissions; fuel consumption; simulated annealing; meta-heuristic; mathematical modelling; optimisation.
International Journal of Supply Chain and Inventory Management, 2017 Vol.2 No.1, pp.20 - 38
Received: 29 Sep 2015
Accepted: 19 Oct 2016
Published online: 22 Aug 2017 *