We develop a new local search approach based on a network ow model that is used to simultaneously evaluate several customer ejection and insertion moves. We use this approach and a direct customer swap procedure to solve the well-known Vehicle Routing Problem. The capacity constraints are relaxed using penalty terms whose parameter values are adjusted according to time and search feedback. Tabu Search is incorporated into the procedure to overcome local optimality. More advanced issues such as intensi cation and diversi cation strategies are developed to provide e ective enhancements to the basic tabu search algorithm. Computational experience on standard test problems is discussed and comparisons with best-known solutions are provided.
We develop a generic tabu search heuristic for solving the well-known vehicle routing problem. This algorithm explores the advantages of simple local search and improvement heuristics as well as a complex meta-heuristic. The solutions generated by these heuristics are selected and assembled by a set-partitioning model to produce superior solutions. Computational experience on standard benchmark problems is discussed and comparisons with other up-to-date heuristic methods are provided.
Tabu Search is a metaheuristic that has proven to be very eective for solving various types of combinatorial optimization problems. To achieve the best results with a tabu search algorithm, signi®cant bene®ts can sometimes be gained by determining preferred values for certain search parameters such as tabu tenures, move selection probabilities, the timing and structure of elite solution recovery for intensi®cation, etc. In this paper, we present and implement some new ideas for ®ne-tuning a tabu search algorithm using statistical tests. Although the focus of this work is to improve a particular tabu search algorithm developed for solving a telecommunications network design problem, the implications are quite general. The same ideas and procedures can easily be adapted and applied to other tabu search algorithms as well. #
One of the private line network design problems in the telecommunications industry is to interconnect a set of customer locations through a ring of end offices so as to minimize the total tariff cost and provide reliability. We develop a Tabu Search method for the problem that incorporates long term memory, probabilistic move selections, hierarchical move evaluation, candidate list strategies and an elite solution recovery strategy. Computational results for test data show that the Tabu Search heuristic finds optimal solutions for all test problems that can be solved exactly by a branch-and-cut algorithm, while running about three orders of magnitude faster than the exact algorithm. In addition, for larger size problems that cannot be solved exactly, the tabu search algorithm outperforms the best local search heuristic currently available. The performance gap favoring Tabu Search increases significantly for more difficult problem instances.digital data service, telecommunications network design, traveling salesman problem, tabu search, heuristic
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.