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Titlebook: Meta-Heuristics; Theory and Applicati Ibrahim H. Osman (Programme Chair),James P. Kelly Book 1996 Kluwer Academic Publishers 1996 Optimiza

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Comparison of Heuristic Algorithms for the Degree Constrained Minimum Spanning Tree,at can be incident to vertices of the graph. In this paper we develop several heuristics, including simulated annealing, neural networks, greedy and greedy random algorithms for constructing such trees. We compare the computational performance of all of these approaches against the performance of an
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An Aggressive Search Procedure for the Bipartite Drawing Problem, minimization is a fundamental aesthetic criterion to obtain a readable map of a graph. The problem of minimizing the number of arc crossings in a bipartite graph (BDP) is NP-complete. In this paper we present an aggressive search scheme for the BDP based on the Intensification, Diversification and
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Heuristic Algorithms for Single Processor Scheduling with Earliness and Flow Time Penalties,earliness penalty. The objective is to minimize the total cost incurred by the penalties. The problem is NP-hard in the strong sense. Exact enumerative algorithms from the literature can solve random instances with . ≤ 50. We study a tabu search approach to the approximate solution of the problem an
发表于 2025-3-31 02:00:47 | 显示全部楼层
Heuristics for the Optimal Control of Thermal Energy Storage,gy storage system. A mixed integer programming model was used to validate the findings of the DP-based heuristic. To expedite the search procedure, a second heuristic was developed that determines the approximate value of the two search parameters. The DP algorithm then searches within a smaller dom
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Combining the Large-Step Optimization with Tabu-Search: Application to The Job-Shop Scheduling Probdefined as follows: given a set of machines and a set of jobs, the objective is to construct a schedule which minimizes the time necessary to complete all the jobs. We also present some diversification strategies for the tabu-search methods and relate them with the large-step optimization method. Re
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Job-Shop Scheduling by Simulated Annealing Combined with Deterministic Local Search,olving JSSPs based on simulated annealing (SA), a stochastic local search, enhanced by shifting bottleneck (SB), a problem specific deterministic local search. In our method new schedules are generated by a variant of Giffler and Thompson’s active scheduler with operation permutations on the critica
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Cybernetic Optimization by Simulated Annealing: An Implementation of Parallel Processing Using Probthe same or related combinatorial optimization problems and are coupled by a . (.). The . is used to generate an error signal for use in feedback control. Control over the search process is achieved by using the error signal to modulate the temperature parameter. Other aspects of control theory, suc
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A simulated annealing algorithm for the computation of marginal costs of telecommunication links, be defined for any given topology. The limits of a computation linked to a particular optimal network configuration led us to consider statistical mechanics methods originally used in combinatorial optimization. Probabilistic properties such as thermostatistical persistency ensure the convergence o
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