A Multi-Model Estimation of Distribution Algorithm for Agent Routing Problem in Multi-Point Dynamic Task

Sai Lu, Bin Xin*, Lihua Dou, Ling Wang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

7 Citations (Scopus)

Abstract

The agent routing problem in multi-point dynamic task (ARP-MPDT) is a multi-task routing problem of a mobile agent. In this problem, there are multiple tasks to be carried out in different locations. As time goes on, the state of each task will change nonlinearly. The agent must go to the task points in tum to perform the tasks, and the execution time of each task is related to the state of the task point when the agent arrives at the point. ARP-MPDT is a typical NP-hard optimization problem. In this paper, we establish the nonlinear ARP-MPDT model. A multi-model estimation of distribution algorithm (EDA) employing node histogram models (NHM) and edge histogram models (EHM) in probability modeling is used to solve the ARP-MPDT. The selection ratio of NHM and EHM probability models is adjusted adaptively. Finally, performance of the algorithm for solving the ARP-MPDT problem is verified by the computational experiments.

Original languageEnglish
Article number8484163
Pages (from-to)2468-2473
Number of pages6
JournalChinese Control Conference, CCC
Volume2018-January
DOIs
Publication statusPublished - 2018
Event37th Chinese Control Conference, CCC 2018 - Wuhan, China
Duration: 25 Jul 201827 Jul 2018

Keywords

  • Estimation of distribution algorithm
  • Multi-model
  • Multi-point dynamic task
  • Routing

Fingerprint

Dive into the research topics of 'A Multi-Model Estimation of Distribution Algorithm for Agent Routing Problem in Multi-Point Dynamic Task'. Together they form a unique fingerprint.

Cite this