Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a well- designed set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that is capable of solving a wide range of combinatorial optimization problems using various tabu search techniques and adaptive strategies. The applications of TSF are demonstrated on the implementation of two NP-hard problems, the Vehicle Routing Problem with Time Windows (VRPTW) and Quadratic Assignment Problem (QAP). We show that TSF is able to obtain quality solutions within reasonable implementation as well as computation time.
Combinatorial optimization, Reusability, Software framework, Tabu search
Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
Metaheuristics: Progress as real problem solvers
T. Ibaraki, K. Nonobe, and M. Yagiura
City or Country
LAU, Hoong Chuin; JIA, Xiaomin; and WAN, Wee Chong.
A generic object-oriented Tabu Search Framework. (2005). Metaheuristics: Progress as real problem solvers. 32, 203-226. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/843
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