Ant Colony Algorithm for Solving Discrete Minimum Constraint Removal (MCR) Problem

Abstract

Abstract:

Abstract： This paper introduces the ant colony algorithm to solve the minimum constraint removal (MCR) problem. The inspired function and pheromone update strategy of the ant colony algorithm(ACO) were improved in the solving process, so that it is no longer easy to fall into local extremum. The simulation results show that the solution quality and convergence rate of the algorithm is better than those of the precise search and greedy algorithm.
Key words：

Key words: discrete minimum constraint removal(MCR)； motion planning problem； robot path planning, ant colony algorithm

CLC Number:

TP 393

XU Bo，MIN Huaqing，XIAO Fangxiong. Ant Colony Algorithm for Solving Discrete Minimum Constraint Removal (MCR) Problem[J]. Journal of Shanghai Jiaotong University, 2015, 49(03): 383-386.

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