.png){kind=icon}
返回
An improved learnable evolution model for solving multi-objective vehicle routing problem with stochastic demand
.png){kind=icon}
OA
AI
DOI：10.1016/j.knosys.2021.107378.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The multi-objective vehicle routing problem with stochastic demand (MO-VRPSD) is much harder to tackle than other traditional vehicle routing problems (VRPs), due to the uncertainty in customer demands and potentially conflicted objectives. In this paper, we present an improved multi-objective learnable evolution model (IMOLEM) to solve MO-VRPSD with three objectives of travel distance, driver remuneration and number of vehicles. In our method, a machine learning algorithm, i.e., decision tree, is exploited to help find and guide the desirable direction of evolution process. To cope with the key issue of route failure caused due to stochastic customer demands, we propose a novel chromosome representation based on priority with bubbles. Moreover, an efficient nondominated sort using a sequential search strategy (ENS-SS) in conjunction with some heuristic operations are leveraged to handle the multi-objective property of the problem. Our algorithm is evaluated on the instances of modified Solomon VRP benchmark. Experimental results show that the proposed IMOLEM is capable to find better Pareto front of solutions and also deliver superior performance to other evolutionary algorithms. (C) 2021 Elsevier B.V. All rights reserved.
Keyword:
Vehicle routing problems
Stochastic demand
Learnable evolution model
Multi-objective evolutionary algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
.png){kind=icon}
Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification基于代价的多目标粒子群算法在分类特征选择中的应用
PREAI
分享收藏Self-Adaptive Particle Swarm Optimization for Large-Scale Feature Selection in Classification自适应粒子群算法在大规模分类特征选择中的应用OAAI
OAAI分享收藏Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints具有时间窗约束的车辆路径和调度问题的算法
PREAI
分享收藏
Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach分类中特征选择的粒子群优化: 一种多目标方法
PREAI
分享收藏
查看更多内容