Abstract
This paper deals with the Single Machine Scheduling Problem with Earliness and Tardiness Penalties, considering distinct due windows and sequence-dependent setup time. Due to its complexity, an adaptive genetic algorithm is proposed for solving it. Many search operators are used to explore the solution space where the choice probability for each operator depends on the success in a previous search. The initial population is generated by the combination between construct methods based on greedy, random and GRASP techniques. For each job sequence generated, a polynomial time algorithm is used for determining the processing initial optimal date to each job. During the evaluation process, the best individuals produced are added to a special group, called elite group. The individuals of this group are submitted to refinement, aiming to improve their quality. Three variations of this algorithm are submitted to computational test. The results show the effectiveness of the proposed algorithm.
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References
Allahverdi, A., Ng, C., Cheng, T.C.E., Kovalyov, M.Y.: A survey of scheduling problems with setup times or costs. European Journal of Operational Research 187, 985–1032 (2008)
Wan, G., Yen, B.P.C.: Tabu search for single machine scheduling with distinct due windows and weighted earliness/tardiness penalties. European Journal of Operational Research 142, 271–281 (2002)
Du, J., Leung, J.Y.T.: Minimizing total tardiness on one machine is np-hard. Mathematics of Operations Research 15, 483–495 (1990)
Lee, C.Y., Choi, J.Y.: A genetic algorithm for job sequencing problems with distinct due dates and general early-tardy penalty weights. Computers and Operations Research 22, 857–869 (1995)
Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedures. Journal of Global Optimization 6, 109–133 (1995)
Gomes Jr., A.C., Carvalho, C.R.V., Munhoz, P.L.A., Souza, M.J.F.: Um método heurístico híbrido para a resolução do problema de sequenciamento em uma máquina com penalidades por antecipação e atraso da produção. In: Anais do XXXIX Simpósio Brasileiro de Pesquisa Operacional - XXXIX SBPO, Fortaleza, Brazil, pp. 1649–1660 (2007)
Prais, M., Ribeiro, C.C.: An application to a matrix decomposition problem in tdma traffic assignmen. INFORMS - Journal on Computing 12, 164–176 (2000)
Liaw, C.F.: A branch-and-bound algorithm for the single machine earliness and tardiness scheduling problem. Computers and Operations Research 26, 679–693 (1999)
Mazzini, R., Armentano, V.A.: A heuristic for single machine scheduling with early and tardy costs. European Journal of Operational Research 128, 129–146 (2001)
Rabadi, G., Mollaghasemi, M., Anagnostopoulos, G.C.: A branch-and-bound algorithm for the early/tardy machine scheduling problem with a common due-date and sequence-dependent setup time. Computers and Operations Research 31, 1727–1751 (2004)
Rosa, B.F., Souza, M.J.F., Souza, S.R.: Formulações de programação matemática para o problema de sequenciamento em uma máquina com janelas de entrega distintas e tempo de preparação dependentes da sequência de produção. In: Anais do XXXII Congresso Nacional de Matemática Aplicada e Computacional – CNMAC 2009, Cuiabá (2009)
Penna, P.H.V.: Um algoritmo heurístico híbrido para minimizar os custos com a antecipação e o atraso da produção em ambientes com janelas de entrega e tempos de preparação dependentes da sequência de produção. In: Dissertação de mestrado, Programa de Pós-Graduação em Engenharia Mineral, Escola de Minas, UFOP, Ouro Preto (2009)
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Ribeiro, F.F., Souza, M.J.F., de Souza, S.R. (2010). An Adaptive Genetic Algorithm to the Single Machine Scheduling Problem with Earliness and Tardiness Penalties. In: da Rocha Costa, A.C., Vicari, R.M., Tonidandel, F. (eds) Advances in Artificial Intelligence – SBIA 2010. SBIA 2010. Lecture Notes in Computer Science(), vol 6404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16138-4_21
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DOI: https://doi.org/10.1007/978-3-642-16138-4_21
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