Yard crane scheduling in a container terminal for the trade-off between efficiency and energy consumption |
| |
| Affiliation: | 1. Liaoning Key Laboratory of Manufacturing System and Logistics, The Logistics Institute, Northeastern University, Shenyang 110819, China;2. School of Business and Economics, Loughborough University, Leicestershire LE11 3TU, UK;1. Rotterdam School of Management, Erasmus University, Rotterdam, The Netherlands;2. School of Management, University of Science and Technology of China, Hefei, China;3. Mechanical Engineering, Systems Engineering, Eindhoven University of Technology, The Netherlands;1. Transport and Mobility Laboratory, École Polytechnique Fédérale de Lausanne, Switzerland;2. Department of Civil Engineering, National University of Singapore, Singapore;3. The Logistics Institute – Asia Pacific, National University of Singapore, Singapore;1. Logistics Research Center, Shanghai Maritime University, Shanghai 200135, China;2. School of Economics & Management, Shanghai University of Electric Power, Shanghai 200090, China |
| |
| Abstract: | ![]()
Green transportation has recently been the focus of the transportation industry to sustain the development of global economy. Container terminals are key nodes in the global transportation network and energy-saving is a main goal for them. Yard crane (YC), as one type of handling equipment, plays an important role in the service efficiency and energy-saving of container terminals. However, traditional methods of YC scheduling solely aim to improve the efficiency of container terminals and do not refer to energy-saving. Therefore, it is imperative to seek an appropriate approach for YC scheduling that considers the trade-off between efficiency and energy consumption. In this paper, the YC scheduling problem is firstly converted into a vehicle routing problem with soft time windows (VRPSTW). This problem is formulated as a mixed integer programming (MIP) model, whose two objectives minimize the total completion delay of all task groups and the total energy consumption of all YCs. Subsequently, an integrated simulation optimization method is developed for solving the problem, where the simulation is designed for evaluating solutions and the optimization algorithm is designed for exploring the solution space. The optimization algorithm integrates the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, where the GA is used for global search and the PSO is used for local search. Finally, computational experiments are conducted to validate the performance of the proposed method. |
| |
| Keywords: | Yard crane scheduling Energy consumption Vehicle routing problem Mixed integer programming Simulation optimization Hybrid algorithm |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
