Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Assembly Line Balancing Optimization”

Assembly Line Balancing Optimization Based on Simulation

Xiaobing Pei, Hongyang Cha · 2015

Simulation is often used to model the production process in order to achieve understanding and improve their purpose, to make the text in order to develop the visualization process automation and use ergonomic principles and process layout principles to improve before the aid Em-plant simulation software to improve results after modeling analysis to confirm the feasibility of optimization and more conducive to the production managers to understand the current situation.

Cited by 2Open access

Assembly line optimization: balancing and part feeding

Masood Fathi · Dialnet (Universidad de la Rioja) · 2014

La linea de montaje para procesos de fabricacion de productos ha sido estudiada ampliamente. En este estudio se centra en dos aspectos importantes: el equilibrado de la linea y el problema de su abastecimiento. Equilibrar una linea de montaje significa asignar las tareas a las estaciones de trabajo cumpliendo una serie de restricciones (por ejemplo: relaciones de precedencia, tiempo de ciclo, etc.). De esta manera, los trabajadores tienen una carga de trabajo similar y el tiempo requerido en cada estacion de trabajo es parecido. El aprovisionamiento a la linea de montaje implica planificar el suministro de los materiales necesarios para la fabricacion a las estaciones de la linea de manera que no se produzcan roturas de stock. El aprovisionamiento a linea es un problema mixto en el que se combina la planificacion y la teoria de decision ya que hay que decidir los materiales se suministran, la cantidad de cada material y el momento adecuado en que se suministran para optimizar los objetivos cumpliendo una serie de restricciones. El problema de equilibrado de lineas de montaje es un problema conocido y estudiado. Sin embargo, el problema de abastecimiento a linea de montaje es un problema que hasta hace poco tiempo no ha sido abordado pero que ultimamente esta despertando gran interes tanto en la industria como en el mundo academico debido a la cada dia mayor complejidad de los procesos de produccion junto con unas mayores exigencias de adecuacion a las necesidades especificas de cada cliente. Todo esto lleva a que el aprovisionamiento se convierta en una cuestion critica. En este trabajo se abordan tanto el equilibrado de la linea como el problema de abastecimiento poniendo mas enfasis en el abastecimiento debido a su novedad. En problema de equilibrado se aplica a una linea de montaje en forma de U y se aborda con un nuevo metaheuristico basado en el procedimiento de Simulated Annealing y en el que se busca la optimizacion de dos objetivos: el numero de estaciones de trabajo (o eficiencia de la linea) y el equilibrio de eficiencia. El problema de abastecimiento a linea el estudio se centra en el suministro de una linea de montaje de tipo mixto que se gestiona siguiendo los principios del Just-In-Time basado en un problema real surgido en una empresa de fabricacion de automoviles. Dada la novedad del problema primero se presenta el modelo matematico (un modelo de Programacion Entera Mixto) al que se anaden dos extensiones. Para encontrar soluciones se presentan tres nuevos algoritmos para resolver el modelo basico y cada una de las extensiones del modelo. El modelo basico se resuelve utilizando un nuevo metaheuristico que se basa en Simulated Annealing. La primera extension se aborda utilizando la tecnica ACO (Ant Colony Ootimization) y la segunda con un nuevo algoritmo PSO hibrido (Particle Swarm Optimization). En ambos casos el objetivo era minimizar tanto el numero de viajes como el nivel de inventario. El algoritmo propuesto para el problema de equilibrado de linea se prueba solucionado una serie de problemas estandar y comparando la solucion con la mejor solucion encontrada en la bibliografia. Los algoritmos propuestos para el problema de abastecimiento a linea se probaron con una serie de ejemplos generados de diferentes tamanos y dos casos reales proporcionados por una planta productora de automoviles. Los resultados obtenidos se compararon con la mejor solucion proporcionada con CPLEX. Los resultados muestran que en ambos problemas los algoritmos desarrollados proporcionan soluciones buenas en un tiempo corto de computacion.

Cited by 0

Assembly line balancing with buffers by multiple criteria optimization

Behnam Malakooti · International Journal of Production Research · 1994

Abstract One of the problems in the design of multi-station lines is the allocation of different work elements to various workstations. This problem is called Assembly Line Balancing (ALB). The failure of workstations and other unforeseen circumstances can result in unnecessary idling of the production line. In order to improve the production rate of such systems, buffer storage of certain capacities can be allocated between each pair of workstations. In this paper, ALB with buffers is formulated as a Single Criterion Decision Making as well as a Multiple Criteria Decision Making problem. In the single objective problem, the cycle time is given and the optimal number of workstations and buffer sizes is obtained to minimize the total cost. In the Multiple Criteria problem, several criteria (objectives) are defined. These objectives are the number of workstations, their buffer sizes, the cycle time and the total cost of operation with buffers. We demonstrate how the set of efficient (nondominated) alternatives for the multiple criteria problem can be generated. The paper also describes how the best alternative can be selected through the use of existing interactive multiple criteria methods. Several examples are solved and the results of computational experiments are provided.

Cited by 39

Assembly line balancing problem using Particle Swarm Optimization algorithm

Yonglin Wang, Ping Zeng, Li Luowei et al. · 2010

Assembly Line Balancing (ALB) is one of the important problems of production/operations management area. Due to the NP-hard nature of the ALB problem, heuristics are generally used to solve real life problems. This paper presents an approach, based on Particle Swarm Optimization (PSO) algorithm, to effectively address the assembly line balance problem with the complicating factors of parallel workstations. The method of linearly decreasing the inertia weight of the PSO (LDWPSO) is used in this paper to compare with the standard PSO. Experimental results show that the LDWPSO algorithm is superior to the standard PSO on some assembly line balancing problem.

Cited by 1

A complex garment assembly line balancing using simulation‐based optimization

Ocident Bongomin, Josphat Igadwa Mwasiagi, Eric Oyondi Nganyi et al. · Greater South Information System · 2020

Abstract The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is important for the apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity. This study proposed assembly line balancing problem (ALBP) for complex garment assembly line using simulation‐based optimization under stochastic task times. The proposed ALBP solution approach aimed at minimizing the cycle time for a given number of workstations with consideration of constraints on number of resources, precedence relations, and resource types. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 69 workstations was considered. The discrete event simulation of the trouser assembly line was developed using Arena simulation software. The local optimal solution was obtained from simulation experiments which was adopted for the optimization process. The OptQuest tool was used to solve a single objective optimization with discrete control values. The results showed that the average throughput increased by 30% for local optimal line balancing and 55% for global optimal line balancing. Consequently, the cycle time reduced by 23% and 36%, respectively.

Cited by 0Open access

Genetic Algorithms for Combinatorial Optimization: The Assembly Line Balancing Problem

Anderson, E.J., Ferris, M.C, Cambridge Univ. (United Kingdom). Management Studies Group · OpenGrey (Institut de l'Information Scientifique et Technique) · 1991

Genetic algorithms are one example of the use of a random element within an algorithm for combinatorial optimization. We consider the application of the genetic algorithm to a particular problem, the Assembly Line Balancing Problem. A general description of genetic algorithms is given, and their specialized use on our test-bed problems is discussed. We carry out extensive computational testing to find appropriate values for the various parameters associated with this genetic algorithm. These experiments underscore the importance of the correct choice of a scaling parameter and mutation rate to ensure the good performance of a genetic algorithm. We also describe a parallel implementation of the genetic algorithm and give some comparisons between the parallel and serial implementations. Both versions of the algorithm are shown to be effective in producing good solutions for problems of this type (with appropriately chosen parameters). Subject classifications: Programming: combinatorial ...

Cited by 2

Graph-based Optimization for Assembly Line Balancing Incorporating Metabolic Restrictions

Joana R. Almeida, Ana Moura, João Almeida et al. · 2025

Manual assembly processes remain a fundamental aspect of the manufacturing industry, primarily due to the dexterity and adaptability of human workers. However, the repetitive and physically demanding nature of these tasks highlights the need for an ergonomic and well-balanced workload, as poor ergonomics can also contribute to errors. This paper aims to automate the assembly line balancing process for a real-world case study. A new multi-objective Assembly Line Balancing Problem (ALBP) formulation is proposed, minimizing both workload variance and variance in workers’ energy expenditure across workstations while accounting for daily fluctuations in the number of operators. The proposed metabolic and time-sensitive assembly line balancing method integrates caloric considerations to reduce long-term risks of Work-Related Musculoskeletal Disorders (WMSDs). Using a graph-based approach, the framework ensures that precedence constraints are met while optimizing task assignments to minimize cycle time and metabolic cost per operator. To improve accuracy in estimating energy expenditure, this study employs the Methods-Time Measurement - Universal Analyzing System (MTM-UAS), which decomposes tasks into standardized motion elements. The methodology is validated through a real-world case study at Bosch Thermotechnology in Portugal, assigning tasks while minimizing the trade-offs between worker fatigue and production goals. The code to validate this study is publicly available at https://github.com/joaorafaelalmeida/line-balancing-algorithm.

Cited by 0

A Complex Garment Assembly Line Balancing Using Simulation-based Optimization

Ocident Bongomin, Josphat Igadwa, Eric Oyondi Nganyi et al. · Greater South Information System · 2020

The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous.Therefore, it is paramount important to apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity.This study aims at achieving an optimal trouser assembly line balancing using simulation-based optimization via design of experiment.The empirical study is conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 72 operations is considered.The discrete event simulation of the trouser assembly line is developed using Arena simulation software.The local optimal solution is obtained from simulation experimentation and is adopted for the optimization process.The OptQuest tool is utilized to solve a single objective function (throughput) optimization problem.The results show that average throughput increases from the existing design (490 pieces per day) to local optimal design (638) and global optimal design (762).Consequently, the line efficiency increases from 61.2% to 79.7% to 95.2% respectively.The high increase in line efficiency and average throughput confirms the suitability assembly line balancing using simulation-based optimization via design of experiment.

Cited by 0Open access

A complex garment assembly line balancing using simulation‐based optimization

Ocident Bongomin, Josphat Igadwa Mwasiagi, Eric Oyondi Nganyi et al. · Engineering Reports · 2020

Abstract The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is important for the apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity. This study proposed assembly line balancing problem (ALBP) for complex garment assembly line using simulation‐based optimization under stochastic task times. The proposed ALBP solution approach aimed at minimizing the cycle time for a given number of workstations with consideration of constraints on number of resources, precedence relations, and resource types. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 69 workstations was considered. The discrete event simulation of the trouser assembly line was developed using Arena simulation software. The local optimal solution was obtained from simulation experiments which was adopted for the optimization process. The OptQuest tool was used to solve a single objective optimization with discrete control values. The results showed that the average throughput increased by 30% for local optimal line balancing and 55% for global optimal line balancing. Consequently, the cycle time reduced by 23% and 36%, respectively.

Cited by 26Open access

A Three-Stage Optimization Method for Assembly Line Balancing Problem

Qidong Yin, Xiaochuan Luo · IEEE Access · 2020

Considering the characteristics of multimodels production pattern on assembly line, the assembly line balancing problem which is non-deterministic polynomial hard becomes more challenging to complete. In this article, we propose a reformulation of simple assembly line balancing problem based on Dantzig-Wolfe decomposition. New models of the master problem and subproblems in this algorithm are built. We implement a branching rule which is suited to seeking integer solutions of the problem. A new three-stage branch-and-price algorithm is designed to accelerate the process of searching the branch-and-bound tree. Extensive computational experiments on benchmark data sets, as well as a real industry case are conducted. The numerical results validate the feasibility and effectiveness of the proposed method which performs efficiently on various cases. Effects on optimization results considering the characteristics of the instance sets are analyzed. Results show that the three-stage branch-and-price algorithm is superior to the classic branch-and-price algorithm in terms of solution quality and computing time.

Cited by 4Open access

Genetic Algorithms for Combinatorial Optimization: The Assembly Line Balancing Problem

Ferris, Michael, Anderson, Edward · Minds at UW (University of Wisconsin) · 2013

Genetic algorithms are one example of the use of a random element within an algorithm for combinatorial optimization. We consider the application of the genetic algorithm to a particular problem, the Assembly Line Balancing Problem. A general description of genetic algorithms is given, and their specialized use on our test-bed problems is discussed. We carry out extensive computational testing to find appropriate values for the various parameters associated with this genetic algorithm. These experiments underscore the importance of the correct choice of a scaling parameter and implementation of the genetic algorithm and give some comparisons between the parallel and serial implementations. Both versions of the algorithm are shown to be effective in producing good solutions for problems of this type (with appropriately chosen parameters).

Cited by 0Open access

A Novel Assembly Line Balancing Optimization Algorithm based on PSOSA

Xiaomei Hu, Yubin Wang, Yangyang Zhang et al. · 2015

Assembly line is widely used in manufacturing system and assembly line balancing problem directly affects the productivity of the whole manufacturing system. In the actual situation of assembly process, optimizing a certain goal in the process of actual assembly individually may cause the neglect of relevance of balance goals, so a dual-objective optimization model is proposed. Although there are many ways to solve the assembly line balancing problem, most of them have a slow convergence speed and poor optimize result. A PSOSA hybrid optimization algorithm is put forward to improve the solution quality. The Metropolis criterion of SA algorithm is integrated into PSO algorithm to overcome the precocious phenomenon of PSO and long optimization time of SA. So the PSOSA hybrid optimization algorithm has the advantages of PSO and SA algorithm. The simulation results show the feasibility and effectiveness of the assembly line balancing optimization algorithm based on PSOSA algorithm.

Cited by 1Open access

OPTIMIZATION OF ASSEMBLY LINE LAY-OUT BY COMPUTER-AIDED CHOICE OF ASSEMBLY METHODS AND LINE BALANCING

Alain Delchambre, Fabrice Pellichero, Emanuel Falkenauer et al. · 2023

This paper presents an integrated method for the design of logical lay-out of assembly lines. It proposes a computer-aided tool to choose the assembly method (manual, hard automated or robotized) for all the assembly operations which have to be performed and assign them to workstations along the line by minimizing the number of stations.<br> After an overview of related works, the paper presents a line balancing method developed on the basis of Grouping Genetic Algorithms (Genetic Algorithms heavily modified to suit grouping problems) to design the logical lay-out of the line.<br> The second part of the paper is devoted to the classification of the main criteria used by the decision-aid tool developed for the choice of the assembly method.<br> The third part of the paper describes the link between the decision-aid tool and the line-balancing software. Finally, conclusions and guidelines for further work are presented.

Cited by 2

Metaheuristic optimization in solving assembly line balancing problems: A short review

Fatini Dalili Mohammed, Mohd Zakimi Zakaria, Mohammad Fadzli Ramli et al. · AIP conference proceedings · 2021

Recently assembly line balancing (ALB) is an ultimate focus issue in manufacturing industries for optimizing both common goals which were the number of workstations and the production rate. Metaheuristic is one of optimization problem-independent technique. This paper focusses on the short review of metaheuristic optimization in solving assembly line balancing problems. Hence, to produce a summary of the review, this paper selects some publications for the past 3 years from year 2016 to 2019. From the review shows the metaheuristic optimization that often used are Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Differential Evaluation (DE), Evolutionary Algorithm (EA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). Besides, GA is most frequently used to solve ALB problems. Finally, recommendation for future research for solving ALB Problems using metaheuristic optimization are discussed.

Cited by 1