A Meta-heuristic Model for Optimizing Goods Transportation Costs in Road Networks based on Particle Swarm Optimization
Pages : 354-361
Road transportation network system plays a significant role in transportation of goods with economical aspects. Most manufacturers’ products and costumers’ needs are transported by transport organizations. But, one of the most concern of many goods transport organizations is to reduce the high costs of transporting goods that imminently impose heavy expenditures and accordingly lessen presentation of an acceptable service to the costumers. Many efficient optimization methods such as particle swarm optimization (PSO) and genetic algorithms (GA) which optimize costs (serviceability, tax, repair of vehicles, fueling, etc.) should be taken into account. The aim of this study is to optimize goods transportation costs from origin to destination centers via PSO Algorithm. This algorithm quickly finds paths with the lowest costs. After applying the algorithm, the results will be categorized into separate equations. Also, from the statistical view, the most optimized equation will be selected. Therefore, an optimal rate in the range of 0.90% and 1.54% has been introduced as a minimizing formula for total monthly costs while the population of vehicles is growing. This formula affects positively reduction of goods transportation costs for a high optimal rate in this paper.
Keywords: Road transportation network system; Goods transportation costs; Transportation network optimization; PSO algorithm
Article published in International Journal of Current Engineering and Technology, Vol.7, No.2 (April-2017)