A Comparison of Heuristics for Mean Flow Time Open Shop Scheduling

Bräsel, Heidemarie; Herms, A.; Mörig, Marc; Tautenhahn, Thomas; Tusch, Jan; Werner, Frank; Willenius, Per

doi:10.3182/20060517-3-fr-2903.00072

Cited by 1 publication

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several benchmark problems from the literature have been solved to optimality for the first time by this algorithm. Brasel et al [14] investigate OSS under minimization of total completion time and propose three types of heuristics based on matching heuristics, priority dispatching rules as well as insertion and appending algorithms combined with beam search. They also present a new encoding scheme, named rank matrices.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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)

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Andresen et al [20] solve OSS with two metaheuristics, simulated annealing and genetic algorithms. Like [14], they use rank matrix to encode a solution. Recently, Roshanaei et al [30] considers the SDST OSS and propose a simulated annealing with variable neighborhood search.…”

Section: Introductionmentioning

confidence: 99%