A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented. The algorithm is based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions. Computational experiments (up to 2,000 operations) show that the algorithm not only finds shorter makespans than the best approximation approaches but also runs in shorter time. It solves the well-known 10 \times 10 hard benchmark problem within 30 seconds on a personal computer.scheduling, heuristics, job-shop, taboo search

The job shop scheduling problem with the makespan criterion is a certain NP-hard case from OR theory having excellent practical applications. This problem, having been examined for years, is also regarded as an indicator of the quality of advanced scheduling algorithms. In this paper we provide a new approximate algorithm that is based on the big valley phenomenon, and uses some elements of so-called path relinking technique as well as new theoretical properties of neighbourhoods. The proposed algorithm owns, unprecedented up to now, accuracy, obtainable in a quick time on a PC, which has been confirmed after wide computer tests.

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This paper deals with a classic job-shop scheduling problem with the makespan criterion. Some properties of the fast algorithm TSAB of Nowicki and Smutnicki, as well as properties of the solution space, have been discussed and examined. Next, by introducing the original method of diversification, TSAB has been embedded in more advanced algorithmic framework i-TSAB, which has far analogy to path relinking technique. Newly proposed algorithm is faster and has better accuracy than TSAB, runs within time of minutes on a PC and already in preliminary tests provides 23 new upper bounds among 35 unsolved yet common Taillard's benchmarks.

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