Now showing 1 - 5 of 5
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    Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs
    (01-06-2004) ;
    Ziegler, Hans
    The problem of scheduling in permutation flowshops is considered with the objective of minimizing the makespan, followed by the consideration of minimization of total flowtime of jobs. Two ant-colony optimization algorithms are proposed and analyzed for solving the permutation flowshop scheduling problem. The first algorithm extends the ideas of the ant-colony algorithm by Stuetzle [Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT '98), vol. 3, Verlag Mainz, Aachen, Germany, 1998, p. 1560], called max-min ant system (MMAS), by incorporating the summation rule suggested by Merkle and Middendorf [Proceedings of the EvoWorkshops 2000, Lecture Notes in Computer Science No. 1803, Springer-Verlag, Berlin, 2000, p. 287] and a newly proposed local search technique. The second ant-colony algorithm is newly developed. The proposed ant-colony algorithms have been applied to 90 benchmark problems taken from Taillard [European Journal of Operational Research 64 (1993) 278]. First, a comparison of the solutions yielded by the MMAS and the two ant-colony algorithms developed in this paper, with the heuristic solutions given by Taillard [European Journal of Operational Research 64 (1993) 278] is undertaken with respect to the minimization of makespan. The comparison shows that the two proposed ant-colony algorithms perform better, on an average, than the MMAS. Subsequently, by considering the objective of minimizing the total flowtime of jobs, a comparison of solutions yielded by the proposed ant-colony algorithms with the best heuristic solutions known for the benchmark problems, as published in an extensive study by Liu and Reeves [European Journal of Operational Research 132 (2001) 439], is carried out. The comparison shows that the proposed ant-colony algorithms are clearly superior to the heuristics analyzed by Liu and Reeves. For 83 out of 90 problems considered, better solutions have been found by the two proposed ant-colony algorithms, as compared to the solutions reported by Liu and Reeves. © 2003 Elsevier B.V. All rights reserved.
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    Two ant-colony algorithms for minimizing total flowtime in permutation flowshops
    (01-06-2005) ;
    Ziegler, Hans
    The problem of scheduling in flowshops with the objective of minimizing total flowtime is studied. For solving the problem two ant-colony algorithms are proposed and analyzed. The first algorithm refers to some extent to ideas by Stuetzle [Stuetzle, T. (1998). An ant approach for the flow shop problem. In: Proceedings of the sixth European Congress on intelligent techniques and soft computing (EUFIT '98) (Vol. 3) (pp. 1560-1564). Aachen: Verlag Mainz] and Merkle and Middendorf [Merkle, D., & Middendorf, M. (2000). An ant algorithm with a new pheromone evaluation rule for total tardiness problems. In: Proceedings of the EvoWorkshops 2000, lecture notes in computer science 1803 (pp. 287-296). Berlin: Springer]. The second algorithm is newly developed. The proposed ant-colony algorithms have been applied to 90 benchmark problems taken from Taillard [Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285]. A comparison of the solutions yielded by the ant-colony algorithms with the best heuristic solutions known for the benchmark problems up to now, as published in extensive studies by Liu and Reeves [Liu, J., & Reeves, C.R. (2001). Constructive and composite heuristic solutions to the P//ΣCi scheduling problem. European Journal of Operational Research, 132, 439-452, and Rajendran and Ziegler [Rajendran, C., & Ziegler, H. (2004). Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. European Journal of Operational Research, 155, 426-438], shows that the presented ant-colony algorithms are better, on an average, than the heuristics analyzed by Liu and Reeves and Rajendran and Ziegler. © 2004 Elsevier Ltd. All rights reserved.
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    An ant-colony optimization algorithm for minimizing the completion-time variance of jobs in flowshops
    (01-06-2006)
    Gajpal, Yuvraj
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    The problem of scheduling in permutation flowshops with the objective of minimizing the completion-time variance of jobs is considered and solved by making use of ant-colony optimization (ACO) algorithms. ACO is an algorithmic approach, inspired by the foraging behavior of real ants, which can be applied to solve combinatorial optimization problems. A new ant-colony algorithm (NACO) has been developed in this paper to solve the flowshop scheduling problem. The objective is to minimize the completion-time variance of jobs. Two existing ant-colony algorithms and the proposed ant-colony algorithm have been compared with an existing heuristic for scheduling with the objective of minimizing the completion-time variance of jobs. It is found that the proposed ant-colony algorithm gives promising and better results, on an average, as compared to those solutions given by the existing ant-colony algorithms and the existing heuristic for the permutation flowshop scheduling problem under study. © 2005 Elsevier B.V. All rights reserved.
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    A fast ant-colony algorithm for single-machine scheduling to minimize the sum of weighted tardiness of jobs
    (01-01-2005)
    Holthatis, O.
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    The problem of scheduling on a single machine is considered in this paper with the objective of minimizing the sum of weighted tardiness of jobs. A new ant-colony optimization (ACO) algorithm, called fast ACO (FACO), is proposed and analysed for solving the single-machine scheduling problem. By considering the benchmark problems available in the literature for analysing the performance of algorithms for scheduling on a single machine with the consideration of weighted tardiness of jobs, we validate the appropriateness of the proposed local-search schemes and parameter settings used in the FACO. We also present a comparison of the requirements of CPU time for solving the single-machine total-weighted tardiness problem by the FACO and the existing algorithms. © 2005 Operational Research Society Ltd. All rights reserved.
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    A two-phase metaheuristic approach for solving Economic Lot Scheduling Problems
    (01-01-2009)
    Chandrasekaran, C.
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    Chetty, O. V.Krishnaiah
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    Hanumanna, D.
    In this paper, economic lot scheduling problem is investigated using time-varying lot sizes approach. The process of finding the best production sequence consists of two-phase implementation of metaheuristics. In the first phase, we propose a genetic algorithm that makes use of the proposed new lower bound to arrive at the good set of production frequencies of products for ELSP without/with backorders. In the second phase, the best sequence of part production is achieved by using the above set of frequencies and employing a GA and an ant-colony algorithm. Computational experiments reveal the effectiveness of the two-phase approach over the conventional single-phase approach. Copyright © 2009, Inderscience Publishers.