scholarly journals Multi-Manned Assembly Line Balancing: Workforce Synchronization for Big Data Sets through Simulated Annealing

2021 ◽  
Vol 11 (6) ◽  
pp. 2523
Author(s):  
Francesco Pilati ◽  
Emilio Ferrari ◽  
Mauro Gamberi ◽  
Silvia Margelli
Keyword(s):  
Simulated Annealing ◽  
Assembly Line ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Assembly Line Balancing ◽  
Task Assignment ◽  
Computation Time ◽  
Mixed Integer ◽  
Solution Quality ◽  
Line Design

The assembly of large and complex products such as cars, trucks, and white goods typically involves a huge amount of production resources such as workers, pieces of equipment, and layout areas. In this context, multi-manned workstations commonly characterize these assembly lines. The simultaneous operators’ activity in the same assembly station suggests considering compatibility/incompatibility between the different mounting positions, equipment sharing, and worker cooperation. The management of all these aspects significantly increases the balancing problem complexity due to the determination of the start/end times of each task. This paper proposes a new mixed-integer programming model to simultaneously optimize the line efficiency, the line length, and the workload smoothness. A customized procedure based on a simulated annealing algorithm is developed to effectively solve this problem. The aforementioned procedure is applied to the balancing of the real assembly line of European sports car manufacturers distinguished by 665 tasks and numerous synchronization constraints. The experimental results present remarkable performances obtained by the proposed procedure both in terms of solution quality and computation time. The proposed approach is the practical reference for efficient multi-manned assembly line design, task assignment, equipment allocation, and mounting position management in the considered industrial fields.

scholarly journals A Mathematical Model and a Simulated Annealing Algorithm for Balancing Multi-manned Assembly Line Problem with Sequence-Dependent Setup Time

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Wucheng Yang ◽  
Wenming Cheng
Keyword(s):  
Simulated Annealing ◽  
Assembly Line ◽  
Simulated Annealing Algorithm ◽  
Assembly Line Balancing ◽  
Setup Time ◽  
Mixed Integer ◽  
Sequence Dependent ◽  
Sequence Dependent Setup Time ◽  
Annealing Algorithm ◽  
Sequence Dependent Setup

Multi-manned assembly lines have been widely applied to the industrial production, especially for large-sized products such as cars, buses, and trucks, in which more than one operator in the same station simultaneously performs different tasks in parallel. This study deals with a multi-manned assembly line balancing problem by simultaneously considering the forward and backward sequence-dependent setup time (MALBPS). A mixed-integer programming is established to characterize the problem. Besides, a simulated annealing algorithm is also proposed to solve it. To validate the performance of the proposed approaches, a set of benchmark instances are tested and the lower bound of the proposed problem is also given. The results demonstrated that the proposed algorithm is quite effective to solve the problem.

Mixed-model multi-manned assembly line balancing problem: a mathematical model and a simulated annealing approach

2017 ◽  
Vol 37 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Abdolreza Roshani ◽  
Farnaz Ghazi Nezami
Keyword(s):  
Simulated Annealing ◽  
Assembly Line ◽  
Mixed Model ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Mixed Integer ◽  
Computational Time ◽  
Content Type ◽  
Mip Model ◽  
Assembly Line Balancing Problem

Purpose This paper aims to study a generalized type of mixed-model assembly line with multi-manned workstations where multiple workers simultaneously perform different tasks on the same product. This special kind of assembly line is usually utilized to assemble different models of large products, such as buses and trucks, on the same production line. Design/methodology/approach To solve the mixed-model multi-manned assembly line balancing problem optimally, a new mixed-integer-programming (MIP) model is presented. The proposed MIP model is nondeterministic polynomial-time (NP)-hard, and as a result, a simulated annealing (SA) algorithm is developed to find the optimal or near-optimal solution in a small amount of computation time. Findings The performance of the proposed algorithm is examined for several test problems in terms of solution quality and running time. The experimental results show that the proposed algorithm has a satisfactory performance from computational time efficiency and solution accuracy. Originality/value This research is the very first study that minimizes the number of workers and workstations simultaneously, with a higher priority set for the number of workers, in a mixed-model multi-manned assembly line setting using a novel MIP model and an SA algorithm.

scholarly journals A Hybrid Simulated Annealing Heuristic for Multistage Heterogeneous Fleet Scheduling with Fleet Sizing Decisions

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Bing Li ◽  
Xinyu Yang ◽  
Hua Xuan
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Initial Solution ◽  
Mixed Integer ◽  
Greedy Heuristic ◽  
Allocation Scheme ◽  
Heterogeneous Fleet ◽  
Fleet Sizing ◽  
Vehicle Allocation

This paper deals with multistage heterogeneous fleet scheduling with fleet sizing decisions (MHFS-FSD). This MHFS-FSD attempts to integrate vehicles allocation and fleet sizing decisions considering the vehicle routing of multiple vehicle types. The problem is formulated as mixed integer programming model. The matrix formulation denoting vehicle allocation scheme is explored according to the characteristic of this problem. Generating vehicle allocation scheme with greedy heuristic procedure (VA-GHP) as initial solution of problem is presented. The USP-IVA method to update the initial solution generated by VA-GHP approach is developed. And then, incorporating VA-GHP and USP-IVA into simulated annealing algorithm, a novel heuristic called HSAH-GHP&IVA is proposed. Finally, some experiments are designed to test the proposed heuristic and the results show that the heuristic can generate reasonably good solutions in short CPU times.

scholarly journals A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongtao Hu ◽  
Yiwei Wu ◽  
Tingsong Wang
Keyword(s):  
Continuous Casting ◽  
Molten Steel ◽  
Assignment Problem ◽  
Programming Model ◽  
Task Assignment ◽  
Solution Algorithm ◽  
Mixed Integer ◽  
Computational Time ◽  
Solution Quality ◽  
Task Assignment Problem

The steelmaking and continuous-casting (SCC) process in integrated iron and steel enterprises can be described as two stages: the upstream stage and downstream stage. Raw materials are transformed into molten steel in the upstream stage, while the downstream stage is responsible for transforming molten steel which is released at regular intervals and has a limited time for being turned into slabs. This article focuses on the task assignment problem in the downstream stage within the given information resulting from the upstream stage. This problem is formulated as a nonlinear mixed-integer programming model aimed at minimizing total tardiness within the resource constraints and time windows constraints for the tasks. An improved solution algorithm based on particle swam optimization is developed to efficiently solve the proposed model. Finally, computational experiments are implemented to evaluate the performance of the solution algorithm in terms of solution quality and computational time.

A simulated annealing algorithm for multi-manned assembly line balancing problem

2013 ◽  
Vol 32 (1) ◽  
pp. 238-247 ◽  
Author(s):  
Abdolreza Roshani ◽  
Arezoo Roshani ◽  
Abdolhassan Roshani ◽  
Mohsen Salehi ◽  
Azadeh Esfandyari
Keyword(s):  
Simulated Annealing ◽  
Assembly Line ◽  
Simulated Annealing Algorithm ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Annealing Algorithm ◽  
Assembly Line Balancing Problem
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