A genetic algorithm approach for balancing two-sided assembly lines with setups

2019 ◽  
Vol 39 (5) ◽  
pp. 827-839 ◽  
Author(s):  
Yilmaz Delice
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Complex Structure ◽  
Real Life ◽  
Setup Time ◽  
Assembly Lines ◽  
Content Type ◽  
Sequence Dependent ◽  
Time Required ◽  
First Time

Purpose This paper aims to discuss the sequence-dependent forward setup time (FST) and backward setup time (BST) consideration for the first time in two-sided assembly lines. Sequence-dependent FST and BST values must be considered to compute all of the operational times of each station. Thus, more realistic results can be obtained for real-life situations with this new two-sided assembly line balancing (ALB) problem with setups consideration. The goal is to obtain the most suitable solution with the least number of mated stations and total stations. Design/methodology/approach The complex structure it possesses has led to the use of certain assumptions in most of the studies in the ALB literature. In many of them, setup times have been neglected or considered superficially. In the real-life assembly process, potential setup configurations may exist between each successive task and between each successive cycle. When two tasks are in the same cycle, the setup time required (forward setup) may be different from the setup time required if the same two tasks are in consecutive cycles (backward setup). Findings Algorithm steps have been studied in detail on a sample solution. Using the proposed algorithm, the literature test problems are solved and the algorithm efficiency is revealed. The results of the experiments revealed that the proposed approach finds promising results. Originality/value The sequence-dependent FST and BST consideration is applied in a two-sided assembly line approach for the first time. A genetic algorithm (GA)-based algorithm with ten different heuristic rules was used in this proposed model.

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.

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.

A genetic algorithm for supermarket location problem

2015 ◽  
Vol 35 (1) ◽  
pp. 122-127 ◽  
Author(s):  
Mohammed Alnahhal ◽  
Bernd Noche
Keyword(s):  
Genetic Algorithm ◽  
Mixed Model ◽  
Location Problem ◽  
Programming Model ◽  
Fixed Costs ◽  
Assembly Lines ◽  
Content Type ◽  
Mixed Model Assembly Lines ◽  
Mutation Operators ◽  
First Time

Purpose – This purpose of this paper is to investigate the location problem of supermarkets, feeding by material the mixed model assembly lines using tow trains. It determines the number and the locations of these supermarkets to minimize transportation and inventory fixed costs of the system. Design/methodology/approach – This is done using integer programming model and real genetic algorithm (RGA) in which custom chromosomes representation, two custom mating and two custom mutation operators were proposed. Findings – The performance of RGA is very good since it gives results that are very close or identical to the optimal ones in reasonable CPU time. Research limitations/implications – The study is applicable only if a group of supermarkets feed the same assembly line. Originality/value – For the first time in supermarket location problem, limitation on availability of some areas for possible supermarkets ' locations and capacity of the supermarkets were taken into consideration.

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.

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.

Dynamic testing resource allocation modeling for multi-release software using optimal control theory and genetic algorithm

2020 ◽  
Vol 37 (6/7) ◽  
pp. 1049-1069
Author(s):  
Vijay Kumar ◽  
Ramita Sahni
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Resource Allocation ◽  
Real Life ◽  
Theoretic Approach ◽  
Numerical Illustration ◽  
Data Set ◽  
Allocation Model ◽  
Content Type ◽  
Software Firms

PurposeThe use of software is overpowering our modern society. Advancement in technology is directly proportional to an increase in user demand which further leads to an increase in the burden on software firms to develop high-quality and reliable software. To meet the demands, software firms need to upgrade existing versions. The upgrade process of software may lead to additional faults in successive versions of the software. The faults that remain undetected in the previous version are passed on to the new release. As this process is complicated and time-consuming, it is important for firms to allocate resources optimally during the testing phase of software development life cycle (SDLC). Resource allocation task becomes more challenging when the testing is carried out in a dynamic nature.Design/methodology/approachThe model presented in this paper explains the methodology to estimate the testing efforts in a dynamic environment with the assumption that debugging cost corresponding to each release follows learning curve phenomenon. We have used optimal control theoretic approach to find the optimal policies and genetic algorithm to estimate the testing effort. Further, numerical illustration has been given to validate the applicability of the proposed model using a real-life software failure data set.FindingsThe paper yields several substantive insights for software managers. The study shows that estimated testing efforts as well as the faults detected for both the releases are closer to the real data set.Originality /valueWe have proposed a dynamic resource allocation model for multirelease of software with the objective to minimize the total testing cost using the flexible software reliability growth model (SRGM).

Coloured stochastic Petri nets modelling for the reliability and maintenance analysis of multi-state multi-unit systems

2014 ◽  
Vol 25 (4) ◽  
pp. 476-490 ◽  
Author(s):  
Zhouhang Wang ◽  
Maen Atli ◽  
H. Kondo Adjallah
Keyword(s):  
Petri Nets ◽  
Complex Structure ◽  
Real Life ◽  
Simulation Models ◽  
Decision Makers ◽  
Stochastic Petri Nets ◽  
Repairable Systems ◽  
Content Type ◽  
Markov Graphs ◽  
Maintenance Policies

Purpose – The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs. Design/methodology/approach – The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size. Findings – Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system. Research limitations/implications – The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered. Practical implications – The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies. Originality/value – The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.

Adjustment mode decision based on support vector data description and evidence theory for assembly lines

2018 ◽  
Vol 118 (8) ◽  
pp. 1711-1726 ◽  
Author(s):  
Youlong Lv ◽  
Wei Qin ◽  
Jungang Yang ◽  
Jie Zhang
Keyword(s):  
Assembly Line ◽  
Historical Data ◽  
Classification Model ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Vector Data ◽  
Assembly Lines ◽  
Content Type ◽  
Input Layer ◽  
Multi Classification

PurposeThree adjustment modes are alternatives for mixed-model assembly lines (MMALs) to improve their production plans according to constantly changing customer requirements. The purpose of this paper is to deal with the decision-making problem between these modes by proposing a novel multi-classification method. This method recommends appropriate adjustment modes for the assembly lines faced with different customer orders through machine learning from historical data.Design/methodology/approachThe decision-making method uses the classification model composed of an input layer, two intermediate layers and an output layer. The input layer describes the assembly line in a knowledge-intensive manner by presenting the impact degrees of production parameters on line performances. The first intermediate layer provides the support vector data description (SVDD) of each adjustment mode through historical data training. The second intermediate layer employs the Dempster–Shafer (D–S) theory to combine the posterior classification possibilities generated from different SVDDs. The output layer gives the adjustment mode with the maximum posterior possibility as the classification result according to Bayesian decision theory.FindingsThe proposed method achieves higher classification accuracies than the support vector machine methods and the traditional SVDD method in the numerical test consisting of data sets from the machine-learning repository and the case study of a diesel engine assembly line.Practical implicationsThis research recommends appropriate adjustment modes for MMALs in response to customer demand changes. According to the suggested adjustment mode, the managers can improve the line performance more effectively by using the well-designed optimization methods for a specific scope.Originality/valueThe adjustment mode decision belongs to the multi-classification problem featured with limited historical data. Although traditional SVDD methods can solve these problems by providing the posterior possibility of each classification result, they might have poor classification accuracies owing to the conflicts and uncertainties of these possibilities. This paper develops a novel classification model that integrates the SVDD method with the D–S theory. By handling the conflicts and uncertainties appropriately, this model achieves higher classification accuracies than traditional methods.

China's tech giants face difficult transition

2018 ◽  
Keyword(s):  
Complex Structure ◽  
Test Case ◽  
Content Type ◽  
Leadership Transitions ◽  
Main Challenge ◽  
20Th Anniversary ◽  
Top Manager ◽  
First Time ◽  
Difficult Transition ◽  
Important Test

Subject The future of Chinese internet conglomerate Alibaba after the forthcoming retirement of its founder. Significance Jack Ma, founder and chairman of China’s internet giant Alibaba Group, has announced that he will resign from his position on September 10, 2019, the company’s 20th anniversary. This will be the first time any major Chinese tech tycoon has handed over the reins. It will be an important test case for both business and political reasons. Impacts The main challenge now will be managing the complex structure into which Alibaba has evolved. A more collective management could make Alibaba less vulnerable should any individual top manager fall foul of the authorities. Ma’s departure will likely create a template for other Chinese tech businesses to plan and manage inevitable leadership transitions.

Balancing a mixed-model assembly line with unskilled temporary workers: algorithm and case study

2018 ◽  
Vol 38 (4) ◽  
pp. 511-523 ◽  
Author(s):  
Dongwook Kim ◽  
Dug Hee Moon ◽  
Ilkyeong Moon
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Mixed Model ◽  
Hybrid Genetic Algorithm ◽  
Temporary Workers ◽  
Labor Costs ◽  
Content Type ◽  
Mixed Model Assembly Line ◽  
Mixed Model Assembly

PurposeThe purpose of this paper is to present the process of balancing a mixed-model assembly line by incorporating unskilled temporary workers who enhance productivity. The authors develop three models to minimize the sum of the workstation costs and the labor costs of skilled and unskilled temporary workers, cycle time and potential work overloads.Design/methodology/approachThis paper deals with the problem of designing an integrated mixed-model assembly line with the assignment of skilled and unskilled temporary workers. Three mathematical models are developed using integer linear programming and mixed integer linear programming. In addition, a hybrid genetic algorithm that minimizes total operation costs is developed.FindingsComputational experiments demonstrate the superiority of the hybrid genetic algorithm over the mathematical model and reveal managerial insights. The experiments show the trade-off between the labor costs of unskilled temporary workers and the operation costs of workstations.Originality/valueThe developed models are based on practical features of a real-world problem, including simultaneous assignments of workers and precedence restrictions for tasks. Special genetic operators and heuristic algorithms are used to ensure the feasibility of solutions and make the hybrid genetic algorithm efficient. Through a case study, the authors demonstrated the validity of employing unskilled temporary workers in an assembly line.

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