Heuristics and lower bounds for the simple assembly line balancing problem type 1: Overview, computational tests and improvements

Purpose The purpose of this study is to develop an immune genetic algorithm (IGA) to solve the simple assembly line balancing problem of type 1 (SALBP-1). The objective is to minimize the number of workstations and workstation load for a given cycle time of the assembly line. Design/methodology/approach This paper develops a new solution method for SALBP-1, and a user-defined function named ψ(·) is proposed to convert all the individuals to satisfy the precedence relationships during the operation of IGA. Findings Computational experiments suggest that the proposed method is efficient. Originality/value An IGA is proposed to solve the SALBP-1 for the first time.

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

Journal of Open Innovation Technology Market and Complexity ◽

10.3390/joitmc6010021 ◽

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.

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Firing sequences backward algorithm for simple assembly line balancing problem of type 1

Computers & Industrial Engineering ◽

10.1016/j.cie.2011.02.001 ◽

2011 ◽

Vol 60 (4) ◽

pp. 830-839 ◽

Cited By ~ 20

Author(s):

Ozcan Kilincci

Keyword(s):

Assembly Line ◽

Assembly Line Balancing ◽

Line Balancing ◽

Assembly Line Balancing Problem ◽

Simple Assembly

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An Improved Ant Colony Optimization for Large-Scale Simple Assembly Line Balancing Problem of Type-1

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.159.51 ◽

2012 ◽

Vol 159 ◽

pp. 51-55 ◽

Cited By ~ 4

Author(s):

Qiao Xian Zheng ◽

Yuan Xiang Li ◽

Ming Li ◽

Qiu Hua Tang

Keyword(s):

Ant Colony Optimization ◽

Assembly Line ◽

Assembly Line Balancing ◽

Ant Colony ◽

Line Balancing ◽

Test Problems ◽

Selection Mechanism ◽

Assembly Line Balancing Problem ◽

Simple Assembly

An improvement ant colony optimization(ACO) is proposed to solve the simple assembly line balancing problem of type-1 (SALBP-1) which aims to minimize the number of workstations for a given cycle time of assembly line. In the algorithm, three heuristic factors and two pheromones: (1) the pheromone between task and station, (2) the pheromone among tasks, are introduced to design the selection mechanism which is used to select task for station. The task assignment mechanism is proposed to assign suitable tasks to station. Ants select task based on selection mechanism, and then assign suitable one to station according to assignment mechanism. The result of literature test problems indicates the effectiveness of the proposed algorithm.

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