Improved Tabu Search Research Articles

An Improved Tabu Search for Economic Dispatch with Multiple Minima

This paper develops an improved tabu search algorithm (ITS) for economic dispatch (ED) with noncontinuous and nonsmooth cost functions. ITS employs a flexible memory system to avoid the entrapment in a local minimum, and developed the ideal of "distance" to the fitness to accelerate optimization. The new approach extends simple tabu search algorithm (STS) to real valued optimization problem, and applies parallelism to weaken the dependence of the convergence rate of modified tabu search algorithm (MTS) on the initial condition. Effectiveness of the method was compared with many conventional methods. Results show that the proposed algorithm can provide accurate solutions with reasonable performance, and has a great potential for other applications in the power system.

An improved tabu search for economic dispatch with multiple minima

This paper develops an improved tabu search algorithm (ITS) for economic dispatch (ED) with noncontinuous and nonsmooth cost functions. ITS employs a flexible memory system to avoid the entrapment in a local minimum and developed the ideal of "distance" to the fitness to accelerate optimization. The new approach extends simple tabu search algorithm (STS) to real valued optimization problem and applies parallelism to weaken the dependence of the convergence rate of modified tabu search algorithm (NITS) on the initial condition. Effectiveness of the method was compared with many conventional methods. Results show that the proposed algorithm can provide accurate solutions with reasonable performance and has a great potential for other applications in the power system.

Fuzzy associative memories for the computation of the bandwidth of rectangular microstrip antennas with thin and thick substrates

A method based on fuzzy associative memories for calculating the bandwidth of electrically thin and thick rectangular microstrip patch antennas is presented. The design parameters of the fuzzy associative memories are optimally determined by using the classical, modified and improved tabu search algorithms. The theoretical bandwidth results obtained by using the fuzzy associative memories are in very good agreement with the experimental results available in the literature.

An improved Tabu search for the global optimizations of electromagnetic devices

An extended Tabu algorithm with an aspiration factor is proposed. The algorithm is based on the success of techniques such as the memorization of the previously visited subspaces, the systematic diversification as well as the intensification process for neighborhood creations. The numerical results obtained by solving a mathematical test function and the benchmark problem 22 of the TEAM Workshop reported in this paper demonstrate the usefulness of the proposed method.

タブー探索法の改良とスケジューリング問題を用いた評価

タブー探索法の改良とスケジューリング問題を用いた評価

An improved tabu search heuristic for solving facility layout design problems

The design of the facility layout of a manufacturing system, usually formulated and solved as a quadratic assignment problem (QAP), is of tremendous importance for its effective utilization. In this paper we discuss a new implementation of the tabu search metaheuristic to solve the QAP. Our tabu search implementation includes recency-based and long term memory structure, dynamic tabu list size strategies, and intensification and diversification strategies. The tabu search algorithm converges with a reasonable speed from any random initial solution to very good layouts. Our extensive computational experiments, including statistical analysis and library analysis, strongly support the superiority of our tabu search implementation (we refer to it as (CK)) over existing algorithms in the literature.

An improved tabu search approach for solving the job shop scheduling problem with tooling constraints

Flexible manufacturing systems (FMSs) are nowadays installed in the mechanical industry. In such systems, many different part types are produced simultaneously and it is necessary to take tooling constraints into account for finding an optimal schedule. A heuristic method is presented for solving the m-machine, n-job shop scheduling problem with tooling constraints. This method, named TOMATO, is based on an adaptation of tabu search techniques and is an improvement on the JEST algorithm proposed by Widmer in 1991.

The Backboard Wiring Problem: A Placement Algorithm

The Backboard Wiring Problem: A Placement Algorithm