Conflict-Based Search and Improvement Strategies for Solving a New Lexicographic Bi-Objective Multi-Agent Path Finding Problem

Document Type

Conference Proceeding

Publication Date

1-1-2022

Abstract

Multi-Agent Path Finding (MAPF) is an important problem with a variety of applications. Its aim is to find collision-free paths for agents having separate start and goal positions. This work proposes a new lexicographic bi-objective MAPF considering different task types, where agents are divided into two kinds to perform critical and acritical tasks. This is common in practical intelligent warehousing scenarios where a critical/acritical-task-performing agent (called c-agent and a-agent, respectively) may represent a full-load/no-load one or the one conducting urgent/non-urgent tasks. The primary objective is to minimize the sum-of-costs of c-agents, while the secondary objective is to minimize the sum-of-costs of a-agents. Two MAPF algorithms are modified to fit and solve the concerned problem for the first time. Moreover, four improvement strategies are embedded to the proposed algorithms and proved to be effective in solving MAPF problems with different task types.

Identifier

85142721818 (Scopus)

ISBN

[9781665452588]

Publication Title

Conference Proceedings IEEE International Conference on Systems Man and Cybernetics

External Full Text Location

https://doi.org/10.1109/SMC53654.2022.9945343

ISSN

1062922X

First Page

1862

Last Page

1867

Volume

2022-October

Grant

62073069

Fund Ref

National Natural Science Foundation of China

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