Three-Tier Multi-agent Approach for Solving Traveling Salesman Problem

2006 ◽  
pp. 813-817
Author(s):  
Shi-Liang Yan ◽  
Ke-Feng Zhou
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multi Agent

A Multi-agent Approach To Solving Dynamic Traveling Salesman Problem

2009 ◽  
Author(s):  
Andrea Varga ◽  
Camelia Chira ◽  
Dan Dumitrescu ◽  
Barna Laszlo Iantovics ◽  
Enachescu Calin ◽  
...  
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multi Agent

A multi-agent approach for solving traveling salesman problem

2006 ◽  
Vol 11 (5) ◽  
pp. 1104-1108 ◽  
Author(s):  
Zhou Tiejun ◽  
Tan Yihong ◽  
Xing Lining
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multi Agent

scholarly journals Anytime Focal Search with Applications

2018 ◽  
Author(s):  
Liron Cohen ◽  
Matias Greco ◽  
Hang Ma ◽  
Carlos Hernandez ◽  
Ariel Felner ◽  
...  
Keyword(s):  
Traveling Salesman Problem ◽  
State Of The Art ◽  
Search Algorithms ◽  
Combinatorial Problems ◽  
Traveling Salesman ◽  
Experimental Side ◽  
Multi Agent ◽  
Special Case ◽  
Theoretical Side

Focal search (FS) is a bounded-suboptimal search (BSS) variant of A*. Like A*, it uses an open list whose states are sorted in increasing order of their f-values. Unlike A*, it also uses a focal list containing all states from the open list whose f-values are no larger than a suboptimality factor times the smallest f-value in the open list. In this paper, we develop an anytime version of FS, called anytime FS (AFS), that is useful when deliberation time is limited. AFS finds a "good" solution quickly and refines it to better and better solutions if time allows. It does this refinement efficiently by reusing previous search efforts. On the theoretical side, we show that AFS is bounded suboptimal and that anytime potential search (ATPS/ANA*), a state-of-the-art anytime bounded-cost search (BCS) variant of A*, is a special case of AFS. In doing so, we bridge the gap between anytime search algorithms based on BSS and BCS. We also identify different properties of priority functions, used to sort the focal list, that may allow for efficient reuse of previous search efforts. On the experimental side, we demonstrate the usefulness of AFS for solving hard combinatorial problems, such as the generalized covering traveling salesman problem and the multi-agent pathfinding problem.

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