Szczegóły publikacji

Opis bibliograficzny

A new MIP approach for balancing and scheduling of mixed model assembly lines with alternative precedence relations / Tadeusz SAWIK // International Journal of Production Research ; ISSN 0020-7543. — 2024 — vol. 62 iss. 1-2, s. 110-121. — Bibliogr. s. 120-121, Abstr. — Publikacja dostępna online od: 2023-07-13. — Dod. afiliacja: Reykjavik University, Iceland


Autor


Słowa kluczowe

mixed integer programmingmixed-model assembly linealternative precedence relationsbalancing and scheduling

Dane bibliometryczne

ID BaDAP151588
Data dodania do BaDAP2024-03-11
Tekst źródłowyURL
DOI10.1080/00207543.2023.2233621
Rok publikacji2024
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Czasopismo/seriaInternational Journal of Production Research

Abstract

In this paper, a new mixed integer programming (MIP) formulation is developed for balancing and scheduling of mixed model assembly lines with disjunctive precedence constraints among assembly tasks. To represent alternative precedence relations, AND/OR assembly graph was adopted. In case of alternative precedence relations, for each product multiple assembly plans exist, which can be represented by a set of alternative precedence subgraphs and only one of such subgraphs should be selected for each product. As the number of subgraphs exponentially increases with the number of disjunctive relations among the tasks, the computational complexity of simultaneous balancing and scheduling along with the assembly subgraph selection increases with the number of alternative precedence relations. Unlike the other MIP approaches known from the literature, the new model does not need the alternative assembly subgraphs to be to explicitly enumerated as input data and then used for indexing the variables. Instead, a new disjunctive precedence selection and task assignment variable and new constraints are introduced to optimally choose one relation for each subset of alternative precedence relations. The optimal solutions for computational examples of balancing and scheduling problems illustrate a superior performance of the new modelling approach.

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