A Methodology Based on Evolutionary Algorithms to Solve a Dynamic Pickup and Delivery Problem Under a Hybrid Predictive Control Approach

作     者：Munoz-Carpintero, Diego Saez, Doris Cortes, Cristian E. Nunez, Alfredo 

作者机构：Univ Chile Dept Elect Engn Santiago 8370451 Chile Univ Chile Dept Civil Engn Santiago 8370449 Chile Delft Univ Technol Sect Rd & Railway Engn NL-2628 CN Delft Netherlands 

出 版 物：《TRANSPORTATION SCIENCE》 (运输科学)

年 卷 期：2015年第49卷第2期

页      面：239-253页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0823[工学-交通运输工程] 

基　　金：CONICYT/FONDECYT/REGULAR Millennium Institute "Complex Engineering Systems [ICM: P-05-004-F, CONICYT: FBO16] 

主　　题：predictive control dynamic pickup and delivery problem evolutionary algorithms 

摘      要：This paper presents a methodology based on generic evolutionary algorithms to solve a dynamic pickup and delivery problem formulated under a hybrid predictive control approach. The solution scheme is designed to support the dispatcher of a dial-a-ride service, where quick and efficient real-time solutions are needed. The scheme considers different configurations of particle swarm optimization and genetic algorithms within a proposed ad-hoc methodology to solve in real time the nonlinear mixed-integer optimization problem related with the hybrid predictive control approach. These consist of different techniques to handle the operational constraints (penalization, Baldwinian, and Lamarckian repair) and encodings (continuous and integer). For parameter tuning, a new approach based on multiobjective optimization is proposed and used to select and study some of the evolutionary algorithms. The multiobjective feature arises when deciding the parameters with the best trade-off between performance and computational effort. Simulation results are presented to compare the different schemes proposed and to advise conditions for the application of the method in real instances.