Department of Industrial Engineering, Mazandaran University of Science & Technology, Babol, Iran.
Department of Industrial Engineering, Mazandaran University of Science & Technology, Babol, Iran.
Waste Manag. 2018 Jun;76:138-146. doi: 10.1016/j.wasman.2018.03.015. Epub 2018 Mar 26.
In this paper, a novel mathematical model is developed for robust periodic capacitated arc routing problem (PCARP) considering multiple trips and drivers and crew's working time to study the uncertain nature of demand parameter. The objective function of the proposed model aims to minimize total traversed distance and total usage cost of vehicles over a planning period. To solve the problem, an improved hybrid simulated annealing algorithm (SA) is developed based on a heuristic algorithm and an efficient cooling equation. It has been proved that the performance of the proposed algorithm is acceptable in comparison with the exact solution method. Finally, the results have shown the effects of different uncertainty level of the demand parameter on the problem to be considered as a managerial overview in decision making process under uncertainty.
本文针对具有多趟次、多司机和驾驶员及机组人员工作时间的鲁棒周期容量受限弧路由问题(PCARP),开发了一种新的数学模型,以研究需求参数的不确定性。所提出模型的目标函数旨在最小化规划期内总行驶距离和车辆总使用成本。为了解决这个问题,基于启发式算法和有效的冷却方程,开发了一种改进的混合模拟退火算法(SA)。已经证明,与精确求解方法相比,所提出算法的性能是可以接受的。最后,结果表明,不同需求参数不确定性水平对所考虑问题的影响可作为不确定条件下决策过程的管理概述。