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  • 1990-1994  (3)
  • combinatorial optimization  (2)
  • scatter search  (1)
  • Logical testing
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Annals of operations research 41 (1993), S. 1-28 
    ISSN: 1572-9338
    Keywords: Tabu search ; heuristics ; combinatorial optimization ; artificial intelligence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We describe the main features of tabu search, emphasizing a perspective for guiding a user to understand basic implementation principles for solving combinatorial or nonlinear problems. We also identify recent developments and extensions that have contributed to increasing the efficiency of the method. One of the useful aspects of tabu search is the ability to adapt a rudimentary prototype implementation to encompass additional model elements, such as new types of constraints and objective functions. Similarly, the method itself can be evolved to varying levels of sophistication. We provide several examples of discrete optimization problems to illustrate the strategic concerns of tabu search, and to show how they may be exploited in various contexts. Our presentation is motivated by the emergence of an extensive literature of computational results, which demonstrates that a well-tuned implementation makes it possible to obtain solutions of high quality for difficult problems, yielding outcomes in some settings that have not been matched by other known techniques.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1573-7497
    Keywords: Production scheduling ; tabu search ; combinatorial optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this article we study thetabu search (TS) method in an application for solving an important class of scheduling problems. Tabu search is characterized by integrating artificial intelligence and optimization principles, with particular emphasis on exploiting flexible memory structures, to yield a highly effective solution procedure. We first discuss the problem of minimizing the sum of the setup costs and linear delay penalties when N jobs, arriving at time zero, are to be scheduled for sequential processing on a continuously available machine. A prototype TS method is developed for this problem using the common approach of exchanging the position of two jobs to transform one schedule into another. A more powerful method is then developed that employs insert moves in combination with swap moves to search the solution space. This method and the best parameters found for it during the preliminary experimentation with the prototype procedure are used to obtain solutions to a more complex problem that considers setup times in addition to setup costs. In this case, our procedure succeeded in finding optimal solutions to all problems for which these solutions are known and a better solution to a larger problem for which optimizing procedures exceeded a specified time limit (branch and bound) or reached a memory overflow (branch and bound/dynamic programming) before normal termination. These experiments confirm not only the effectiveness but also the robustness of the TS method, in terms of the solution quality obtained with a common set of parameter choices for two related but different problems.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Statistics and computing 4 (1994), S. 131-140 
    ISSN: 1573-1375
    Keywords: Genetic algorithms ; scatter search ; optimization ; mathematical relaxation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We provide a tutorial survey of connections between genetic algorithms and scatter search that have useful implications for developing new methods for optimization problems. The links between these approaches are rooted in principles underlying mathematical relaxations, which became inherited and extended by scatter search. Hybrid methods incorporating elements of genetic algorithms and scatter search are beginning to be explored in the literature, and we demonstrate that the opportunity exists to develop more advanced procedures that make fuller use of scatter search strategies and their recent extensions.
    Type of Medium: Electronic Resource
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