An immune genetic algorithm for simple assembly line balancing problem of type 1

2019 ◽  
Vol 39 (1) ◽  
pp. 113-123 ◽  
Author(s):  
Han-ye Zhang
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Immune Genetic Algorithm ◽  
Content Type ◽  
Assembly Line Balancing Problem ◽  
Simple Assembly ◽  
First Time

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.

A multi-manned assembly line balancing problem with classified teams: a new approach

2016 ◽  
Vol 36 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Hamid Yilmaz ◽  
Mustafa Yilmaz
Keyword(s):  
Design Methodology ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Test Problems ◽  
New Approach ◽  
Content Type ◽  
Line Test ◽  
Assembly Line Balancing Problem ◽  
First Time

Purpose – Within team-oriented approaches, tasks are assigned to teams before being assigned to workstations as a reality of industry. So it becomes clear, which workers assemble which tasks. Design/methodology/approach – Team numbers of the assembly line can increase with the number of tasks, but at the same time, due to physical situations of the stations, there will be limitations of maximum working team numbers in a station. For this purpose, heuristic assembly line balancing (ALB) procedure is used and mathematical model is developed for the problem. Findings – Well-known assembly line test problems widely used in the literature are solved to indicate the effectiveness and applicability of the proposed approach in practice. Originality/value – This paper draws attention to ALB problem in which workers have been assigned to teams in advance due to the need for specialized skills or equipment on the line for the first time.

Multi-manned assembly line balancing problem with balanced load density

2015 ◽  
Vol 35 (1) ◽  
pp. 137-142 ◽  
Author(s):  
Hamid Yilmaz ◽  
Mustafa Yilmaz
Keyword(s):  
Mathematical Model ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Assembly Lines ◽  
Content Type ◽  
Task Load ◽  
Balance Task ◽  
Assembly Line Balancing Problem ◽  
First Time

Purpose – The purpose of this paper is balancing multi-manned assembly lines with load-balancing constraints in addition to conventional ones Most research works about the multi-manned assembly line balancing problems are focused on the conventional industrial measures that minimize total number of workers, number of multi-manned workstations or both. Design/methodology/approach – This paper provides a remedial constraint for the model to balance task load density for each worker in workstations. Findings – Comparisons between the proposed mathematical model and the existing multi-manned mathematical model show a quite promising better task load density performance for the proposed approach. Originality/value – In this paper, a mathematical model that combines the minimization of multi-manned stations, worker numbers and difference of task load density of workers is proposed for the first time.

scholarly journals Time and space multi-manned assembly line balancing problem using genetic algorithm

2021 ◽  
Vol 14 (4) ◽  
pp. 733
Author(s):  
Nessren Zamzam ◽  
Ahmed Elakkad
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Real Life ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Initial Population ◽  
Time And Space ◽  
Task Time ◽  
Assembly Line Balancing Problem ◽  
Simple Assembly

Purpose: Time and Space assembly line balancing problem (TSALBP) is the problem of balancing the line taking the area required by the task and to store the tools into consideration. This area is important to be considered to minimize unplanned traveling distance by the workers and consequently unplanned time waste. Although TSALBP is a realistic problem that express the real-life situation, and it became more practical to consider multi-manned assembly line to get better space utilization, few literatures addressed the problem of time and space in simple assembly line and only one in multi-manned assembly line. In this paper the problem of balancing bi-objective time and space multi-manned assembly line is proposedDesign/methodology/approach: Hybrid genetic algorithm under time and space constraints besides assembly line conventional constraints is used to model this problem. The initial population is generated based on conventional assembly line heuristic added to random generations. The objective of this model is to minimize number of workers and number of stations.Findings: The results showed the effectiveness of the proposed model in solving multi-manned time and space assembly line problem. The proposed method gets better results in solving real-life Nissan problem compared to the literature. It is also found that there is a relationship between the variability of task time, maximum task time and cycle time on the solution of the problem. In some problem features it is more appropriate to solve the problem as simple assembly line than multi-manned assembly line.Originality/value: It is the first article to solve the problem of balancing multi-manned assembly line under time and area constraint using genetic algorithm. A relationship between the problem features and the solution is found according to it, the solution method (one sided or multi-manned) is defined.

A multiple rule-based genetic algorithm for cost-oriented stochastic assembly line balancing problem

2019 ◽  
Vol 39 (1) ◽  
pp. 124-139 ◽  
Author(s):  
Ahad Foroughi ◽  
Hadi Gökçen
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Superior Performance ◽  
Line Balancing ◽  
Rule Based ◽  
Content Type ◽  
Assembly Line Balancing Problem ◽  
The Cost ◽  
Stochastic Assembly

Purpose This research aims to address the cost-oriented stochastic assembly line balancing problem (ALBP) and propose a chance-constrained programming model. Design/methodology/approach The cost-oriented stochastic ALBP is solved for small- to medium-sized problems. Owing to the non-deterministic polynomial-time (NP)-hardness problem, a multiple rule-based genetic algorithm (GA) is proposed for large-scale problems. Findings The experimental results show that the proposed GA has superior performance and efficiency compared to the global optimum solutions obtained by the IBM ILOG CPLEX optimization software. Originality/value To the best of the authors’ knowledge, only one study has discussed the cost-oriented stochastic ALBP using the new concept of cost. Owing to the NP-hard nature of the problem, it was necessary to develop a heuristic or meta-heuristic algorithm for large data sets; this research paper contributes to filling this gap.

Simple assembly line balancing problem of Type 1 with grey demand and grey task durations

2019 ◽  
Vol 9 (4) ◽  
pp. 401-414 ◽  
Author(s):  
Oğuzhan Ahmet Arık ◽  
Erkan Köse ◽  
Jeffrey Forrest
Keyword(s):  
Mathematical Model ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Grey Theory ◽  
Content Type ◽  
Task Durations ◽  
Simple Assembly ◽  
And Task

Purpose The purpose of this paper is to present a mixed integer programming model for simple assembly line balancing problems (SALBP) with Type 1 when the annual demand and task durations are uncertain and encoded with grey numbers. Design/methodology/approach Grey theory and grey numbers are used for illustrating the uncertainty of parameters in an SALBP, where the objective is to minimize the total number of workstations. The paper proposes a 0-1 mathematical model for SALBP of Type 1 with grey demand and grey task durations. Findings The uncertainty of the demand and task durations are encoded with grey numbers and a well-known 0-1 mathematical model for SALBP of Type 1 is modified to find the minimum number of workstations in order to meet both the lower and upper bounds of the uncertain demand. The results obtained from the proposed mathematical model show a task-workstation assignment that does not distribute precedence relations among tasks and workstations and the sum of task durations in each single workstation is less than or equal to the grey cycle time. Originality/value The grey theory and grey numbers have not been previously used to identify uncertainties in assembly line balancing problems. Therefore, this study provides an important contribution to the literature.

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.

scholarly journals An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem

2019 ◽  
Vol 37 (2) ◽  
pp. 501-521 ◽  
Author(s):  
Masood Fathi ◽  
Amir Nourmohammadi ◽  
Amos H.C. Ng ◽  
Anna Syberfeldt ◽  
Hamidreza Eskandari
Keyword(s):  
Genetic Algorithm ◽  
Variable Neighborhood Search ◽  
Assembly Line ◽  
Real Life ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Neighborhood Search ◽  
Improved Genetic Algorithm ◽  
Content Type ◽  
Assembly Line Balancing Problem

Purpose This study aims to propose an efficient optimization algorithm to solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision-makers aim to design an efficient assembly line while satisfying a set of constraints. Design/methodology/approach An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP to optimize the number of stations and the workload smoothness. Findings To evaluate the performance of the IGA, it is used to solve a set of well-known benchmark problems and a real-life problem faced by an automobile manufacturer. The solutions obtained are compared against two existing algorithms in the literature and the basic genetic algorithm. The comparisons show the high efficiency and effectiveness of the IGA in dealing with ALBPs. Originality/value The proposed IGA benefits from a novel generation transfer mechanism that improves the diversification capability of the algorithm by allowing population transfer between different generations. In addition, an effective variable neighborhood search is used in the IGA to enhance its local search capability.

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