Integration of balancing and preventive maintenance in straight and U-shaped resource-dependent assembly lines: MILP model and memetic algorithm

In enterprises, machines are subject to some unavailable periods resulting in production halts. The consideration of preventive maintenance (PM) and resource assignment in straight and U-shaped assembly lines is of paramount importance. Hence, this paper aims to tackle the integration of PM and bala...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Applied soft computing Ročník 113; s. 107773
Hlavní autori: Zhang, Zikai, Tang, Qiuhua, Qian, Xinbo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.12.2021
Predmet:
Integration optimization
Memetic algorithm
MILP model
Preventive maintenance
Resource dependent assembly line balancing
Memetic algorithm
MILP model
Integration optimization
Resource dependent assembly line balancing
Preventive maintenance
ISSN:1568-4946, 1872-9681
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In enterprises, machines are subject to some unavailable periods resulting in production halts. The consideration of preventive maintenance (PM) and resource assignment in straight and U-shaped assembly lines is of paramount importance. Hence, this paper aims to tackle the integration of PM and balancing problems in straight and U-shaped resource-dependent assembly lines via two new mixed-integer linear programming (MILP) models and a memetic algorithm. In the MILP models, the optimal PM intervals of all machines and all PM scenarios are determined according to the maximization of the availability. In the memetic algorithm, a multi-attribute solution representation, including heuristic rule matrix, task separator set and machine assignment permutation, is designed to build a feasible solution. For this multi-attribute solution representation, this algorithm respectively designs different crossover, mutation and local search operators to exploit the space around the solutions. Finally, five comparison experiments are conducted to prove the effectiveness of the MILP models in small-scale instances and the superiority of the improvements and memetic algorithm in all instances. •All maintenance scenarios are determined according to the maximization of the availability.•Two new mixed-integer linear programming models for SRDALB_PM and URDALB_PM are formulated.•An attempt is made to solve the new problems by memetic algorithm.•The proposed algorithm designs multi-attribute solution representation and multi-operators.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2021.107773