scholarly journals An exact method with decomposition techniques and combinatorial Benders’ cuts for the type-2 multi-manned assembly line balancing problem

2020 ◽  
Vol 7 ◽  
pp. 100163 ◽  
Author(s):  
Adalberto Sato Michels ◽  
Thiago Cantos Lopes ◽  
Leandro Magatão
Keyword(s):  
Assembly Line ◽  
Assembly Line Balancing ◽  
Exact Method ◽  
Line Balancing ◽  
Decomposition Techniques ◽  
Assembly Line Balancing Problem

Assembly Line Balancing Type-2 Using Unequal Multiple Operators

2013 ◽  
Vol 816-817 ◽  
pp. 1169-1173
Author(s):  
Usman Attique ◽  
Abdul Ghafoor ◽  
Riaz Ahmed ◽  
Shahid Ikramullah
Keyword(s):  
Cycle Time ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Computational Effort ◽  
Line Balancing ◽  
Heuristic Methods ◽  
Novel Approach ◽  
Assembly Line Balancing Problem

Various exact and heuristic methods have been proposed for assembly line balancing problem (ALBP) but unequal multiple operators have not been considered much. In this paper we present a novel approach of assembly line balancing Type-2 with unequal multiple operators by using an already developed code in Matlab (Tomlab modeling platform). The adopted approach can be applied at line balancing problems ranging from few to hundreds of work elements to achieve minimum cycle time with very less computational effort.

scholarly journals Simple Assembly Line Balancing Problem Type 2 By Variable Neighborhood Strategy Adaptive Search: A Case Study Garment Industry

2020 ◽  
Vol 6 (1) ◽  
pp. 21
Author(s):  
Ganokgarn Jirasirilerd ◽  
Rapeepan Pitakaso ◽  
Kanchana Sethanan ◽  
Sasitorn Kaewman ◽  
Worapot Sirirak ◽  
...  
Keyword(s):  
Assembly Line ◽  
Assembly Line Balancing ◽  
Black Box ◽  
Line Balancing ◽  
Problem Type ◽  
Adaptive Search ◽  
Assembly Line Balancing Problem ◽  
Simple Assembly

This article aims to minimize cycle time for a simple assembly line balancing problem type 2 by presenting a variable neighborhood strategy adaptive search method (VaNSAS) in a case study of the garment industry considering the number and types of machines used in each workstation in a simple assembly line balancing problem type 2 (SALBP-2M). The variable neighborhood strategy adaptive search method (VaNSAS) is a new method that includes five main steps, which are (1) generate a set of tracks, (2) make all tracks operate in a specified black box, (3)operate the black box, (4) update the track, and (5) repeat the second to fourth steps until the termination condition is met. The proposed methods have been tested with two groups of test instances, which are datasets of (1) SALBP-2 and (2) SALBP-2M. The computational results show that the proposed methods outperform the best existing solution found by the LINGO modeling program. Therefore, the VaNSAS method provides a better solution and features a much lower computational time.

A Heuristic Approach for Type 2 Assembly Line Balancing Problem

2015 ◽  
Vol 789-790 ◽  
pp. 1296-1300
Author(s):  
Bukhari Pakeeza ◽  
Ahmad Riaz ◽  
Muhammad Umer
Keyword(s):  
Assembly Line ◽  
Experimental Testing ◽  
Assembly Line Balancing ◽  
Task Assignment ◽  
Line Balancing ◽  
Cycle Times ◽  
Time In Literature ◽  
Assembly Line Balancing Problem

An assembly system consists of work stations where specific tasks are carried in such a way that last station gives the complete product. An assembly line balancing Problem (ALBP) involves optimally assigning tasks among workstations with respect to some performance objective. ALBP problems are of NP hard nature and in literature; many efforts are there to solve the problem efficiently through heuristics. This paper proposes a heuristic algorithm for solving type 2 ALBP for single objective optimization. The proposed algorithm assigns tasks to a fixed no of stations with objective of minimizing cycle time. In literature, type 2 ALBP is mostly solved through Type 1 problem. However, this paper proposes a direct approach to Type 2 ALBP. The effectiveness is tested through application on Gunther problem of 35 tasks with forty five precedence constraints. The task assignment for six stations is computed and it shows competitive performance. The number of fixed stations is varied and corresponding cycle times are computed. The algorithm is also tested on a real industrial problem of 24 tasks. The experimental testing indicates tendency of the proposed algorithm to give effective optimal results.

An integer-coded differential evolution algorithm for simple assembly line balancing problem of type 2

2016 ◽  
Vol 36 (3) ◽  
pp. 246-261 ◽  
Author(s):  
Haijun Zhang ◽  
Qiong Yan ◽  
Yuanpeng Liu ◽  
Zhiqiang Jiang
Keyword(s):  
Differential Evolution ◽  
Assembly Line ◽  
Differential Evolution Algorithm ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Content Type ◽  
Evolution Algorithm ◽  
Assembly Line Balancing Problem ◽  
Simple Assembly

Purpose This paper aims to develop a new differential evolution algorithm (DEA) for solving the simple assembly line balancing problem of type 2 (SALBP-2). Design/methodology/approach Novel approaches of mutation operator and crossover operator are presented. A self-adaptive double mutation scheme is implemented and an elitist strategy is used in the selection operator. Findings Test and comparison results show that the proposed IDEA obtains better results for SALBP-2. Originality/value The presented DEA is called the integer-coded differential evolution algorithm (IDEA), which can directly deal with integer variables of SALBP-2 on a discrete space without any posterior conversion. The proposed IDEA will be an alternative in evolutionary algorithms, especially for various integer/discrete-valued optimization problems.

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