Mixed-model parallel two-sided assembly line balancing problem: A flexible agent-based ant colony optimization approach

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Assembly lines are frequently used as a production method to assemble complex products. Two-sided assembly lines are utilized to assemble large-sized products (e.g., cars, buses, trucks). Locating two lines in parallel helps improve line efficiency by enabling collaboration between the line workers. This paper proposes a mixed-model parallel two-sided assembly line system that can be utilized to produce large-sized items in an inter-mixed sequence. The mixed-model parallel two-sided line balancing problem is defined and the advantages of utilizing multi-line stations across the lines are discussed. A flexible agent-based ant colony optimization algorithm is developed to solve the problem and a numerical example is given to explain the method systematically. The proposed algorithm builds flexible balancing solutions suitable for any model sequence launched. The dynamically changing workloads of workstations (based on specific product models during the production process) are also explored. A comprehensive experimental study is conducted and the results are statistically analyzed using the well-known paired sample t-test. The test results indicate that the mixed-model parallel two-sided assembly line system reduces the workforce need in comparison with separately balanced mixed-model two-sided lines. It is also shown that the proposed algorithm outperforms the tabu search algorithm and six heuristics often used in the assembly line balancing domain

Balancing parallel assembly lines with disabled workers

[EN] In this paper, we study an assembly line balancing problem that occurs in sheltered worker centres for the disabled, where workers with very different characteristics are present. We are interested in the situation in which complete parallel assembly lines are allowed and name the resulting problem as parallel assembly line worker assignment and balancing problem (PALWABP). This approach enables many new possible worker-tasks assignments, what is beneficial in terms of both labour integration and productivity. We present a linear mixed-integer formulation and two heuristic solution methods: one is based on tabu search and the other is a biased random-key genetic algorithm (BRKGA). Computational results with a large set of instances recently proposed in the literature show the advantages of allowing such alternative line layouts.This research was supported by CAPES-Brazil and MEC-Spain (coordinated project CAPES DGU 258-12/PHB2011-0012-PC) and by FAPESP-Brazil. The authors thank Dr. Marcus Ritt, from Universidade Federal do Rio Grande do Sul (UFRGS - Brazil), for providing the optimal solutions for the serial ALWABP. The authors also thank three anonymous reviewers for their comments which have helped improve this paper.Araujo, FFB.; Costa, AM.; Miralles Insa, CJ. (2015). Balancing parallel assembly lines with disabled workers. European J of Industrial Engineering. 9(3):344-365. https://doi.org/10.1504/EJIE.2015.069343S3443659

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the classical simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.Comment: 18 pages, 1 figur

A mathematical model and genetic algorithm-based approach for parallel two-sided assembly line balancing problem

Copyright © 2015 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning & Control on 27 April 2015, available online: http://dx.doi.org/10.1080/09537287.2014.994685Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature

Balancing and lot-sizing mixed-model lines in the footwear industry

This report describes the full research proposal for the project \Balancing and lot-sizing mixed-model lines in the footwear industry", to be developed as part of the master program in Engenharia Electrotécnica e de Computadores - Sistemas de Planeamento Industrial of the Instituto Superior de Engenharia do Porto. The Portuguese footwear industry is undergoing a period of great development and innovation. The numbers speak for themselves, Portugal footwear exported 71 million pairs of shoes to over 130 countries in 2012. It is a diverse sector, which covers different categories of women, men and children shoes, each of them with various models. New and technologically advanced mixed-model assembly lines are being projected and installed to replace traditional mass assembly lines. Obviously there is a need to manage them conveniently and to improve their operations. This work focuses on balancing and lot-sizing stitching mixed-model lines in a real world environment. For that purpose it will be fundamental to develop and evaluate adequate effective solution methods. Different objectives may be considered, which are relevant for the companies, such as minimizing the number of workstations, and minimizing the makespan, while taking into account a lot of practical restrictions. The solution approaches will be based on approximate methods, namely by resorting to metaheuristics. To show the impact of having different lots in production the initial maximum amount for each lot is changed and a Tabu Search based procedure is used to improve the solutions. The developed approaches will be evaluated and tested. A special attention will be given to the solution of real applied problems. Future work may include the study of other neighbourhood structures related to Tabu Search and the development of ways to speed up the evaluation of neighbours, as well as improving the balancing solution method

Iterative Beam Search for Simple Assembly Line Balancing with a Fixed Number of Work Stations

The simple assembly line balancing problem (SALBP) concerns the assignment of tasks with pre-defined processing times to work stations that are arranged in a line. Hereby, precedence constraints between the tasks must be respected. The optimization goal of the SALBP-2 version of the problem concerns the minimization of the so-called cycle time, that is, the time in which the tasks of each work station must be completed. In this work we propose to tackle this problem with an iterative search method based on beam search. The proposed algorithm is able to obtain optimal, respectively best-known, solutions in 283 out of 302 test cases. Moreover, for 9 further test cases the algorithm is able to produce new best-known solutions. These numbers indicate that the proposed iterative beam search algorithm is currently a state-of-the-art method for the SALBP-2

Development of a heuristic procedure for balancing mixed-model parallel assembly line type II

The single-model assembly line is not efficient for today’s competitive industry because to respond the customer’s expectation, companies need to produce mixedmodel products. On the other hand, using the mixed-model products increases the assembly complexity and makes it difficult to assign tasks to workstations because of the variety in model characteristics. As a result, the mixed-model products suffer from delays, limitations in the line workflow and longer lines. Parallel assembly lines as a production system in ALBPs which consists of a number of assembly lines in a parallel status, which by considering the cycle time of each line certain products are manufactured. This thesis takes advantages of the parallel assembly lines to produce mixed-model in order to assemble more than one model in each parallel assembly line and allocating tasks of models to workstations and balancing each parallel line to reduce the cycle times. To solve these problems, two heuristic algorithms were developed and coded in MATLAB®. The first one allocates each model to only one parallel assembly line and achieves the initial arrangement of tasks with the minimum number of workstations for each line. The second one called Tabu search Mixed-Model Parallel Assembly Line Balancing (TMMPALB), calculates final balancing tasks of different model in parallel lines with optimum cycle time for each line which tasks of each model can be allocated to more than one parallel assembly line through the TMMPALB. The main advantages of employing TS are using a flexible memory structure during the search process, and intensification and diversification strategies, which help to make a comprehensive search in the solution space. Fourteen data sets create 81 test problems that were solved to validate the performance of the TMMPALB. Each test problem consisted of the number of tasks, process time for each task (time unit), and the precedence relationship, minimum number of station and cycle time for each model. By considering that 80 out of the 81 test problems include three models and the remaining one has four models, 244 cycle times is made, which TMMPALB tries to minimize. The computational results showed that 205 cycle times out of the 244 cycle times have been improved. These results demonstrated that by arranging mixed-model through the parallel assembly lines with minimum number of workstations, the minimum cycle times are achieved in comparing with the single line

A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks

[EN] In assembly lines, rework stations are generally used for reprocessing defective items. On the other hand, using rework stations for this purpose only might cause inefficient usage of the resources in this station especially in an assembly line with a low defective rate. In this study, a mixed-integer programming model for cycle time minimization is proposed by considering the use of rework stations for performing parallel tasks. By linearizing the non-linear constraint about parallel tasks using a variate transformation, the model is transformed to a linear-mixed-integer form. In addition to different defective rates, different rework station positions are also considered using the proposed model. The performance of the model is analyzed on several test problems from the related literature.Cavdur, F.; Kaymaz, E. (2020). A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks. 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Heuristics and Lower Bounds for the Simple Assembly Line Balancing Problem Type 1: Overview, Computational Tests and Improvements

Assigning tasks to work stations is an essential problem which needs to be addressed in an assembly line design. The most basic model is called simple assembly line balancing problem type 1 (SALBP-1). We provide a survey on 12 heuristics and 9 lower bounds for this model and test them on a traditional and a lately-published benchmark dataset. The present paper focuses on algorithms published before 2011. We improve an already existing dynamic programming and a tabu search approach significantly. These two are also identified as the most effective heuristics; each with advantages for certain problem characteristics. Additionally we show that lower bounds for SALBP-1 can be distinctly sharpened when merging them and applying problem reduction techniques