Two hybrid meta-heuristics for the finite horizon ELSP in flexible flow lines with unrelated parallel machines

Jenabi, Masoud; Ghomi, S. M. T. Fatemi; Torabi, S. Ali; Karimi, Behrooz

doi:10.1016/j.amc.2006.06.121

Cited by 33 publications

(15 citation statements)

References 22 publications

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“…Another real world application is given in [87], where a real printed circuit board manufacturing system modeled as a 3-stage HFS is approached with GA. The HFS with multiprocessor tasks is studied for the makespan criterion by [175] and by [139] and approached with GA. A GA and a SA were proposed for a fairly complex cyclic scheduling flexible flow line with lot sizing in [85]. Another complex problem with production time windows in flexible flow lines is exposed in [151].…”

Section: Metaheuristicsmentioning

confidence: 99%

“…F Hm, ((P M (k) ) m k=1 ))|avail|several simulation, heuristics, SA [16] F H3, ((P M (k) ) 3 k=1 ))||Cmax agent-based approach [20] F Hm, ((P M (k) ) m k=1 ))|recrc|Ū w MPF, GA, lower bounds,checks processing [47] F Hm, ((P M (k) ) m k=1 ))||Cmax Artificial Immune Systems [91] F Hm, ((P M (k) ) m k=1 ))|blocking, skip|Cmax flow lines, MPF, TS, huristics F H2, ((1 (1) , P 2 (2) ))||Cmax B&B, GA, heuristics [41] F Hm, ((P M (k) ) m k=1 ))|recrc|T w dispatching rules, heuristics [61] F H2, ((1 (1) , P 2 (2) ))|no − wait, (p j = 1) 1 |Cmax exact method [96] F Hm, ((P M (k) ) m k=1 ))||{Cmax,C} review on exact solution methods [121] F H2, ((1 (1) , P M (2) ))|avail|Cmax B&B, heuristics, complexity [38] F H3, ((RM (k) ) 3 k=1 ))|prec, block, S nsd |Cmax MPR-TS [70] F H2, ((P M (k) ) 2 k=1 )||Cmax B&B [88] F Hm, ((P M (k) ) m k=1 ))||Cmax MPR-SA, lower bounds [107] F H2, ((P 2 (1) , 1 (2) ))|batch|Cmax TSP-based heuristics [37] F H3, ((RM (k) ) 3 k=1 ))|S sd , block, prec|Cmax MPF, lower bounds, TS [50] F Hm, ((P M (k) ) m k=1 ))|assign|ĒT TS, special problem [83] F Hm, ((P M (k) ) m k=1 ))|r j |Cost TS, SA, heuristics [85] F Hm, ((RM (k) ) m k=1 ))|lot, skip|Cost GA, SA, flow lines [100] F H3, ((P M (k) ) 3 k=1 ))||Cmax heuristics [151] (1) , P 2 (2) ))|assembly (2) |F heuristics [195] F Hm, ((P M (k) ) m k=1 ))|size jk |Cmax Particle Swarm Optimization [196] F H2, ((1 (1) , P 2 (2) ))|skip (1) |Cmax heuristics 2009 [90] F Hm, ((RM (k) ) m k=1 ))|S sd , r j |αCmax + (1 − α)Ū MPF, heuristics, dispatching rules, GA [95] F H2, ((P M (1) , 1 (2) ))||Cmax heuristics, product-mix [191] F Hm, ((P M (k) ) m k=1 ))|skip, block, reentry|Cmax GA mixed with LS [229] F Hm, ((P M (k) ) m k=1 ))|size jk |Cmax Iterated Greedy (IG) [19] F H2, ((P M (1) , P M (2) ))|batch (2) |Cmax heuris...…”

Section: Research Opportunities and Conclusionmentioning

confidence: 99%

See 1 more Smart Citation

The hybrid flow shop scheduling problem

Ruíz

Vázquez-Rodríguez

2010

European Journal of Operational Research

681

236

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The scheduling of flow shops with multiple parallel machines per stage, usually referred to as the Hybrid Flow Shop (HFS), is a complex combinatorial problem encountered in many real world applications. Given its importance and complexity, the HFS problem has been intensively studied. This paper presents a literature review on exact, heuristic and metaheuristic methods that have been proposed for its solution.The paper discusses several variants of the HFS problem, each in turn considering different assumptions, constraints and objective functions. Research opportunities in HFS are also discussed.

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Section: Metaheuristicsmentioning

confidence: 99%

Section: Research Opportunities and Conclusionmentioning

confidence: 99%

The hybrid flow shop scheduling problem

Ruíz

Vázquez-Rodríguez

2010

European Journal of Operational Research

681

236

View full text Add to dashboard Cite

show abstract

“…However, some products may skip some stages. Jenabi et al (2007) studied the ELDSP in the flexible flow shop with unrelated parallel machines based on common cycle approach and they presented a mixed-integer nonlinear programming (MINLP) model for this problem.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, researchers have had a great attention to the multi-stage production systems, such as flow shop and job shop Ziaeifar et al, 2011) and many researchers considered the ELSP and ELDSP in these production systems (El-Najdawi, 1993;Ouenniche & Boctor, 1998;Ouenniche et al, 1999;Ouenniche & Bertrand, 2001;Ouenniche & Boctor, 2001a;Ouenniche & Boctor, 2001b;Ouenniche & Boctor, 2001c;Fatemi Ghomi & Torabi, 2002;Torabi et al, 2005;Torabi et al, 2006;Jenabi et al, 2007;Torabi & Jenabi, 2009a;Torabi & Jenabi, 2009b).…”

Section: Introductionmentioning

confidence: 99%

An economic lot and delivery scheduling problem with the fuzzy shelf life in a flexible job shop with unrelated parallel machines

Dousthaghi¹,

Tavakkoli–Moghaddam²

2012

ijiec

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This paper considers an economic lot and delivery scheduling problem (ELDSP) in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP) approach. In this paper, a mixed-integer nonlinear programming (MINLP) model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples.

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“…They develop a mixed integer nonlinear program, an optimal enumeration method to solve the problem, and a hybrid genetic algorithm which incorporates a neighbourhood search into a basic genetic algorithm that enables the algorithm to perform genetic search over the subspace of local optima. More recently, Jenabi et al (2007) apply a genetic algorithm with a local improvement procedure to the economic lot sizing and scheduling problem in hybrid flowshops. The results are compared to those of a simulated annealing approach.…”

Section: Genetic Algorithms For Hybrid Flowshop Problemsmentioning

confidence: 99%

Heuristics and metaheuristics for heavily constrained hybrid flowshop problems

Urlings¹

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Es ist nicht genug zu wissen, man muss auch anwenden.Es ist nicht genug zu wollen, man muss auch tun.Knowing is not enough, we must apply.Willing is not enough, we must do.Johann Wolfgang von Goethe, Wilhelm Meisters Wanderjahre, 1821. I ABSTRACT HEURISTICS AND METAHEURISTICS FOR HEAVILY CONSTRAINED HYBRID FLOWSHOP PROBLEMSDue to the current trends in business as the necessity to have a large catalogue of products, orders that increase in frequency but not in size, globalisation and a market that is increasingly competitive, the production sector faces an ever harder economical environment. All this raises the need for production scheduling with maximum efficiency and effectiveness.The first scientific publications on production scheduling appeared more than half a century ago. However, many authors have recognised a gap between the literature and the industrial problems. Most of the research concentrates on optimisation problems that are actually a very simplified version of reality. This allows for the use of sophisticated approaches and guarantees in many cases that optimal solutions are obtained. Yet, the exclusion of real-world restrictions harms the applicability of those methods. What the industry needs are systems for optimised production scheduling that adjust exactly to the conditions in the production plant and that generates good solutions in very little time. This is exactly the objective in this thesis, that is, to treat more realistic scheduling problems and to help closing the gap between the literature and practice.The considered scheduling problem is called the hybrid flowshop problem, which consists in a set of jobs that flow through a number of production stages. At each of the stages, one of the machines that belong to the stage is visited. III IVA series of restriction is considered that include the possibility to skip stages, non-eligible machines, precedence constraints, positive and negative time lags and sequence dependent setup times. In the literature, such a large number of restrictions has not been considered simultaneously before. Briefly, in this thesis a very realistic production scheduling problem is studied.Various optimisation methods are presented for the described scheduling problem. A mixed integer programming model is proposed, in order to obtain optimal solutions for limited cases and in order to analyse the complexity of each of the problem restrictions. In continuation, seven constructive heuristics are presented with the purpose of obtaining fast solutions to the problem in more general cases. Advanced metaheuristic methods are studied in detail, starting with five genetic algorithms that allow studying the effect of the solution representation. Three local search based algorithms are proposed, which is very novel if the elevated complexity of the problem is taken into account. In addition, novel methods are presented that shift the solution representation during the search process in order to acquire near-optimal solutions. The obtained results endorse the use of thes...

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Two hybrid meta-heuristics for the finite horizon ELSP in flexible flow lines with unrelated parallel machines

Cited by 33 publications

References 22 publications

The hybrid flow shop scheduling problem

The hybrid flow shop scheduling problem

An economic lot and delivery scheduling problem with the fuzzy shelf life in a flexible job shop with unrelated parallel machines

Heuristics and metaheuristics for heavily constrained hybrid flowshop problems

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