Title: An efficient hybrid heuristic method for prioritising large transportation projects with interdependent activities
Authors: Saeed A. Bagloee; Madjid Tavana
Addresses: Parsons Overseas Limited, Gulf Tower-B, Oud Metha Road, Dubai, UAE. ' Management Information Systems, Lindback Distinguished Chair of Information Systems, La Salle University, Philadelphia, PA19141, USA
Abstract: Transportation projects are generally large, with limited resources and highly interdependent activities. The complexities and interdependencies apparent in large transportation projects have prohibited effective application of management science and economics methods to these problems. We propose a heuristic method with several hybrid components. We formulate the problem as a Travelling Salesman Problem (TSP). A Neural Network (NN) is used to cope with the interdependency concerns. An algorithm with an iterative process is confined to search for the longest path (most benefit or most reduction in the user-time) in the NN as a solution to the TSP. The solution from each iteration step is utilised to update and train the NN and enhance its prediction. A search engine inspired by the concept of Ant Colony (AC) and hybridised with Genetic Algorithm (GA) is developed to find a suitable solution to the TSP. The hybrid heuristic method proposed in this study is applied to the real data for the city of Winnipeg in Canada to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.
Keywords: TSP; travelling salesman problem; hybrid heuristics; neural networks; ant colony optimisation; ACO; GAs; genetic algorithms; project prioritisation; large transport projects; Winnipeg; Canada.
DOI: 10.1504/IJLSM.2012.044052
International Journal of Logistics Systems and Management, 2012 Vol.11 No.1, pp.114 - 142
Published online: 28 Nov 2014 *
Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article