Heuristics for scheduling in a no-wait open shop with movable dedicated machines

Lin, Hung-Tso; Lee, Hong-Tau; Pan, Wen-Jung

doi:10.1016/j.ijpe.2007.01.005

Cited by 26 publications

(14 citation statements)

References 21 publications

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“…The criterion was to minimise the makespan. Some two-phase heuristic algorithms for the open-shop scheduling problem with movable dedicated machines and without time restrictions were presented by Baccarelli et al (2012), Hosseinabadi et al (2014a, b), Lina et al (2008), Pooranian et al (2011). The aim of these solutions was to reduce the social costs, such as air pollution and traffic congestion.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises

et al. 2015

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The problem of open-shop scheduling includes a set of activities which must be performed on a limited set of machines. The goal of scheduling in open-shop is the presentation of a scheduled program for performance of the whole operation, so that the ending performance time of all job operations will be minimised. The open-shop scheduling problem can be solved in polynomial time when all nonzero processing times are equal, becoming equivalent to edge coloring that has the jobs and workstations as its vertices and that has an edge for every job-workstation pair with a nonzero processing time. For three or more workstations, or three or more jobs, with varying processing times, open-shop scheduling is NP-hard. Different algorithms have been presented for open-shop scheduling so far. However, most of these algorithms have not considered the machine maintenance problem. Whilst in production level, each machine needs maintenance, and this directly influences the assurance reliability of the system. In this paper, a new genetic-based algorithm to solve the open-shop scheduling problem, namely OSGA, is developed. OSGA considers machine maintenance. To confirm the performance of OSGA, it is compared with DGA, SAGA and TSGA algorithms. It is observed that OSGA performs quite well in terms of solution quality and efficiency in small and medium enterprises (SMEs). The results support the efficiency of the proposed method for solving the open-shop scheduling problem, particularly considering machine maintenance especially in SMEs'.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises

et al. 2015

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“…EA optimally solves 12 instances out of 13 instances. After having investigated the general performance of the proposed electromagnetism algorithm, we further evaluate the proposed algorithm against the adaptation of a relevant algorithm, the two-phase solution algorithm (TPSA) of Lin et al (2008). To do so, we use standard benchmarks in the literature, such as those of Taillard (1993), Brucker et al (1997), and Guéret and Prins (1998).…”

Section: Evaluation Of the Metaheuristicmentioning

confidence: 99%

“…They developed a branch-and-bound with some dominance rules as well as a two-phase algorithm. OSNB with movable dedicated machines to minimize total occupation time of all the machines was considered by Lin et al (2008). They introduced a mixed integer nonlinear program to model the problem.…”

Section: Introductionmentioning

confidence: 99%

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An electromagnetism-like metaheuristic for open-shop problems with no buffer

2012

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This paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic based on an electromagnetism algorithm to solve the large-sized problems. The paper conducts two computational experiments. The first includes small-sized instances by which the mathematical model and general performance of the proposed metaheuristic are evaluated. The second evaluates the metaheuristic for its performance to solve some large-sized instances. The results show that the model and algorithm are effective to deal with the problem.

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“…Since he considers a special preemptive case, his model is not adaptable to classical OSS. Lin et al [21] formulate another variant of OSS where jobs are no-wait and there are movable dedicated machines. Unfortunately, this model is non-linear, and consequently ineffective.…”

Section: Introductionmentioning

confidence: 99%

An electromagnetism-like metaheuristic for sequence dependent open shop scheduling

Naderi

Jenabi

Ghomi

et al. 2010

2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)

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Abstract� It is known that in many real industrial settings, some setup is carried out before the process of a job. Usually, the magnitude of this setup depends on the order of two consecutive jobs. In this case, the setup is called sequence-dependent. This paper deals with open shop scheduling with sequence-dependent setup times to minimize the total completion time. We formulate the problem as an effective mixed integer linear programming model that best characterizes and solves to optimality small-sized instances of the problem under consideration. Since the electromagnetism-like metaheuristic (EM) is successfully applied to some NP-hard problems, we have been motivated to employ and assess the effectiveness of EM to solve the open shop with setup times. To further enhance EM, we incorporate a local search engine in form of a fast and simple simulated annealing. In order to evaluate the performance of the proposed algorithms, we design an experiment in which the proposed methods are compared against some algorithms in the literature. The related results are analyzed by statistical tools. The experimental results and statistical analyses demonstrate that our proposed model and EM are effective for the problem.

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Heuristics for scheduling in a no-wait open shop with movable dedicated machines

Cited by 26 publications

References 21 publications

RETRACTED ARTICLE: OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises

RETRACTED ARTICLE: OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises

An electromagnetism-like metaheuristic for open-shop problems with no buffer

An electromagnetism-like metaheuristic for sequence dependent open shop scheduling

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