A Memetic Algorithm for Uncertain Capacitated Arc Routing Problems

被引:0
|
作者
Wang, Juan [1 ]
Tang, Ke [1 ]
Yao, Xin [1 ]
机构
[1] Univ Sci & Technol China, Sch Comp Sci & Technol, NICAL, Hefei 230027, Anhui, Peoples R China
基金
英国工程与自然科学研究理事会;
关键词
UCARP; robust optimization; evolutionary algorithm; ROBUST OPTIMIZATION;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The Capacitated Arc Routing Problem (CARP) is a widely investigated classic combinatorial optimization problem. Being a deterministic model, it is far away from the real world. A more practical problem model of CARP is the Uncertain CARP (UCARP), with the objective of finding a robust solution which performs well in all possible environments. There exist few algorithms for UCARP in previous work. In this paper, a Memetic Algorithm (MA) and its modified version in time consumption for UCARP are proposed. Experimental results on two benchmark test sets show that with an integrated fitness function and a large step-size local search operator, the new MAs show excellent ability to find robust solutions for UCARP. We also present a less time-consuming version of our MA which shows significant advantages in time consumption.
引用
收藏
页码:72 / 79
页数:8
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