A recent survey of production scheduling

Rodammer, Frederick A.; White, K. Preston

doi:10.1109/21.23085

Cited by 210 publications

(54 citation statements)

References 35 publications

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“…This is in line witl1 the view that simulation is an economic way to evaluate alternatives before implementation (Mott and Tumay, 1992), although perhaps not as thorough as tltey claim. In their extensive article on production scheduling approaches, Rodammer and White (1988) reach the conclusion that once a problem has been defined and suitable candidates generated, the performance of candidate schedules could be verified using simulation models. This is the same approach used in the scenario simulation methodology.…”

Section: Discussionmentioning

confidence: 99%

A Scenario Simulation Methodology for Re-engineering Potential Assessment

Lehtonen¹,

Marttila²

1997

Computer Applications in Production and Engineering

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The research objective of this paper is to experiment the applicability of scenario simulation methodology in a paper industry distribution problem. The methodology proved to be able to assess the re-engineering potential by producing quantifiable results for the performance measures. The methodology itself does not provide optimal re-engineering actions. Its function is to assess the improvement potential of re-engineering actions derived elsewhere.

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Section: Discussionmentioning

confidence: 99%

A Scenario Simulation Methodology for Re-engineering Potential Assessment

Lehtonen¹,

Marttila²

1997

Computer Applications in Production and Engineering

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“…ara auxiliar na tomada de decisão gerencial quanto à determinação da escala de produção foram desenvolvidos sistemas de base de dados para administração da compra e estoque de matéria-prima, estoque em processo e capacidade de produção, dentre outras atividades rotineiras de um processo de produção (RODAMMER et al, 1988). Estas ferramentas melhoram a qualidade e a consistência da solução para o planejamento da manufatura e algumas delas incorporam, em maior ou menor grau, recursos que procuram automatizar atividades de programação da produção.…”

Section: Princípio De Operação Das Práticas Industriaisunclassified

O planejamento da manufatura: práticas industriais e métodos de otimização

1998

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Resumo Este trabalho apresenta uma revisão das metodologias mais utilizadas como ferramentas de apoio ao planejamento da produção de sistemas de manufatura. Dentre elas destacam-se as práticas industriais conhecidas como técnicas avaliativas de soluções e os métodos de otimização conhecidos como técnicas gerativas de solução. Procura-se discutir como estas técnicas trabalham e analisar as vantagens e desvantagens de cada uma delas. Na conclusão a otimização é apresentada como uma ferramenta complementar para superar certas deficiências encontradas durante a aplicação das práticas industriais, tornando-se assim essencial ao planejamento da produção.Palavras-chave: MRP, JIT, programação matemática, planejamento da produção.

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“…Traditional approaches to the scheduling problem apply optimization techniques to a mathematical formulation of the problem, and have proven to be intractable even for many idealized situations (Graves, 1981;Rodammer and White, 1988). Strictly mathematical formulations often do not allow consideration of the full range of shop floor attributes, realistic configurations and uncertainties inherent in the problem, and also fail to take into account the high level priorities and goals involved in scheduling (Buxey, 1989).…”

Section: Introductionmentioning

confidence: 99%

Learning by Objectives for Adaptive Shop‐Floor Scheduling*

Bhattacharyya

Kœhler

1998

Decision Sciences

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Effective production scheduling requires consideration of the dynamics and unpredictability of the manufacturing environment. An automated learning scheme, utilizing genetic search, is proposed for adaptive control in typical decentralized factory-floor decision-making. A highlevel knowledge representation for modeling production environments is developed, with facilities for genetic learning within this scheme. A multiagent framework is used, with individual agents being responsible for the dispatch decision making at different work-stations.Learning is with respect to stated objectives, and given the diversity of scheduling goals, the efficacy of the designed learning scheme is judged through its response under different objectives. The behavior of the genetic learning scheme is analyzed, and simulation studies help compare how learning under different objectives impacts certain aggregate measures of system performance.

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A recent survey of production scheduling

Cited by 210 publications

References 35 publications

A Scenario Simulation Methodology for Re-engineering Potential Assessment

A Scenario Simulation Methodology for Re-engineering Potential Assessment

O planejamento da manufatura: práticas industriais e métodos de otimização

Learning by Objectives for Adaptive Shop‐Floor Scheduling*

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