Ants can solve the team orienteering problem

Authors:
Liangjun Ke;Claudia Archetti;Zuren Feng
Affiliations:
State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China;Department of Quantitative Methods, University of Brescia, Brescia, Italy;State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China
Venue:
Computers and Industrial Engineering
Year:
2008

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Abstract

The team orienteering problem (TOP) involves finding a set of paths from the starting point to the ending point such that the total collected reward received from visiting a subset of locations is maximized and the length of each path is restricted by a pre-specified limit. In this paper, an ant colony optimization (ACO) approach is proposed for the team orienteering problem. Four methods, i.e., the sequential, deterministic-concurrent and random-concurrent and simultaneous methods, are proposed to construct candidate solutions in the framework of ACO. We compare these methods according to the results obtained on well-known problems from the literature. Finally, we compare the algorithm with several existing algorithms. The results show that our algorithm is promising.