Heuristics and exact algorithms for solving the Monden problem

Bautista, Joaquı́n; Companys, Ramón; Corominas, Albert

doi:10.1016/0377-2217(94)00165-0

Cited by 95 publications

(94 citation statements)

References 9 publications

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“…The heuristics are first tested with the problem data set given in Bautista et al (1996) and Jin and Wu (2002). The results are presented with 95% confidence level for different structures (part-product combinations) and demand patterns.…”

Section: Computational Results For the Parts Usage Measurementioning

confidence: 99%

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Mixed-model assembly line sequencing using beam search

Erel

Göçgün

Sabuncuoğlu

2007

International Journal of Production Research

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In today's manufacturing environments, companies have to produce a large variety of products in small quantities on a single assembly line. In this paper, we use a beam search (BS) approach to solve the model-sequencing problem of mixed-model assembly lines (MMALs). Specifically, we develop six BS algorithms for part-usage variation and load-leveling performance measures. The results of computational experiments indicate that the proposed BS methods are competitive with the well-known heuristics in the literature. A comprehensive bibliography is also provided.

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Section: Computational Results For the Parts Usage Measurementioning

confidence: 99%

“…Bautista et al (1996) propose a two-stage heuristic to reduce the myopic feature of the GCM. The procedure searches two models for the next two stages to minimize the combined variation (i.e.…”

Section: Existing Solution Methodsmentioning

confidence: 99%

Mixed-model assembly line sequencing using beam search

Erel

Göçgün

Sabuncuoğlu

2007

International Journal of Production Research

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“…This procedure combines features of dynamic programming with features of branch-and-bound algorithms [27]. A review of hybrid meta-heuristics in combinatorial optimization can be found in [28].…”

Section: Preliminariesmentioning

confidence: 99%

“…Graph associated with the problem Similar to ( [18], [27]) can build a linked graph without loops or direct cycles of…”

Section: 2mentioning

confidence: 99%

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A hybrid dynamic programming for solving a mixed-model sequencing problem with production mix restriction and free interruptions

2016

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Abstract. In this article, we propose a hybrid procedure based on bounded dynamic programming (BDP) assisted by linear programming (LP) to solve the mixed-model sequencing problem with workload minimization (MMSP-W) with serial workstations, free interruption of the operations and with production mix restrictions. We performed a computational experiment with 23 instances related to a case study of the Nissan powertrain plant located in Barcelona. The results of our proposal are compared with those obtained by Mixed Integer Linear Programming (MILP).

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ECAS: a collaborative multi-agent system for mixed-model assembly lines programming

Caridi

1999

Global Production Management

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This paper presents a multi-agent model, ECAS, for sequencing a mixed-model assembly line. ECAS implements the concept of deliberative and cooperative agents: the agents contract in order to fmd a solution which overcomes the objectives of the single agents in order to pursue the global optimum of the system. ECAS represents the extension of a previous model by the author, AGENT, which implements deliberative but not cooperative agents. One of the aims of this paper is to compare the results of the two models in order to evaluate the value added by cooperation. Moreover, ECAS performance is compared with other traditional approaches to the same problem.

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Heuristics and exact algorithms for solving the Monden problem

Cited by 95 publications

References 9 publications

Mixed-model assembly line sequencing using beam search

Mixed-model assembly line sequencing using beam search

A hybrid dynamic programming for solving a mixed-model sequencing problem with production mix restriction and free interruptions

ECAS: a collaborative multi-agent system for mixed-model assembly lines programming

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