.png){kind=icon}
返回
A multi-objective Covering Salesman Problem with 2-coverage
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2021.108024.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In a wide range of contexts including military operations, environment monitoring, surveillance in border areas, health care, public safety [1, 2], disaster management, humanitarian relief and blood supply chain, a robust solution of the Covering Salesman Problem (CSP) is necessary. These applications require more than one facilities to cover a given customer (region of interest (ROI)). In this paper, we consider the coverage radius to be fixed and same for each node. Then we propose a multi-objective algorithm based on NSGA-II, in which minimization of tour length and maximization of number of nodes with 2-coverage are considered as the objectives. For implementing the algorithm, an individual chromosome is represented using a one-dimensional array with variable length, and developed a new crossover and a new mutation operator based on the problem and variable length chromosome representation. Numerical examples taken from TSP instances (TSPLIB [3]) with number of nodes ranging from 51 to 150 are solved using the algorithm. For each numerical example, the tour corresponding to the solution with 2-coverage of customer nodes is presented, which shows that the proposed algorithm is effective. Finally, a potential future research direction of this problem is discussed. (C) 2021 Elsevier B.V. All rights reserved.
Keyword:
Covering Salesman Problem
2-coverage
NSGA-II
Multi-objective optimization problem
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
引用论文
Investigation of morphologies and characterization of rare earth metal samarium hexacyanoferrate and its composite with surfactant intercalated graphene oxide for sensor applications.png)
RSC Adv.
RSC Adv.IF0
PREAI
分享收藏
Perturbed Decomposition Algorithm applied to the multi-objective Traveling Salesman Problem扰动分解算法在多目标旅行商问题中的应用
PREAI
分享收藏Multiobjective evolutionary algorithms: A comparative case study and the Strength Pareto approach多目标进化算法: 比较案例研究和强度帕累托方法
PREAI
分享收藏分享收藏
查看更多内容