Genetic algorithm for assembly line balancing

Rubinovitz, Jacob; Levitin, Gregory

doi:10.1016/0925-5273(95)00059-3

Cited by 127 publications

(67 citation statements)

References 4 publications

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“…Simple assembly line balancing problem, the most employed form of line balancing problems, assumes the single-model production, and was considered by a vast number of publications such as Baybars (1986), Saltzman andBaybars (1987), Hoffmann (1992), Rubinovitz and Levitin (1995), Klein and Scholl (1996), Sprecher (1999), Peeters and Degraeve (2006), Gokcen et al (2005), Zhang et al (2007, Liu et al (2008), Nourmohammadi andZandieh (2011).…”

Section: International Journal Of Production Researchmentioning

confidence: 99%

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Research

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Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed by Ozcan et al. (Balancing parallel two-sided assembly lines, International Journal of Production Research, 48 (16), 4767-4784, 2010). The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles explained and discussed.Keywords: mixed-model parallel two-sided assembly lines; assembly line balancing; agent based ant colony optimisation; meta-heuristics; artificial intelligence

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Section: International Journal Of Production Researchmentioning

confidence: 99%

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Research

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“…Thus, we can calculate R e (k,n,t) in the transformed scale by (25), (26) or (27), and the system failure rate α i can be obtained by (18), (19) and (21) with h 0 (t′)=1. Therefore, unless otherwise specified, only the TFR models with an exponential failure time baseline distribution are discussed in this paper.…”

Section: R K N T T T Kmentioning

confidence: 99%

“…components and the exponential failure time distributions can be easily derived as follows. (27) For the TFR models with an arbitrary baseline failure distribution F(t), we can perform the time transformation suggested by Amari et al [3]:…”

Section: Tfr Model For An Exactly K-out-n: F Systemmentioning

confidence: 99%

Reliability analysis and optimization of equal load-sharing k-out-of-n phased-mission systems

Chen¹,

He²,

Wei³

2015

Eksploatacja i Niezawodnosc - Maintenance and Reliability

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Reliability analysis and optimization of equal load-shaRing k-out-of-n phased-mission systems analiza niezawodności oRaz optymalizacja systemów fazowych typu "k z n" o Równym podziale obciążenia elementów składowychThere are many studies on k-out-of-n systems, load-sharing systems (LSS) Słowa kluczowe: Właściwa ścieżka uszkodzeń (AFP), algorytm genetyczny (GA), system fazowy (o zadaniach okresowych) (PMS), Model manipulowanej intensywności uszkodzeń (TFR), Uniwersalna funkcja tworząca (UGF).

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“…Solution flexibility can be determined from precedence matrix by measuring − (flexibility ratio). Higher − indicates less precedence constraints and greater flexibility in generating multiple feasible solutions (Rubinovitz et al, 1995).…”

Section: First Stage Experimentationmentioning

confidence: 99%