Heuristics for energy efficient vehicle routing problem

Abstract

US logistics cost of 1.397 trillion dollars in 2007, which stands for more that 10 percent of the total GDP of the country justifies any attempt of reducing it. Transportation followed by inventory-carrying and logistics administration has the greatest cost share in logistics. A tool which is very critical in transportation planning and can contribute to huge savings if used properly is Vehicle Routing Problem. Near optimum vehicle routs which are designed by outstanding heuristics and experts could contribute significantly to cost saving. Another important issue which directly affects logistics and transportation is energy consumption. Energy consumption and energy saving plans are hot topics everywhere nowadays. Issues such as green house effect, global warming effect and oil resources termination are great global concerns. This research tries to modify vehicle routing problem heuristics and make them sensitive to the issue of energy consumption. Traditional VRP heuristics and solution methods have tried to minimize total distance traveled of vehicles as the main objective function, while energy consumption minimization is the objective function of energy efficient VRP heuristics in this research. Two heuristics are modified in an “Energy Efficient” manner, nearest neighbor algorithm and saving algorithm. The proposed heuristics are examined with several benchmark problems from literature and are found to be efficient and effective both in terms of total distance travelled and energy consumption.