New Matrix Methodology for Algorithmic Transparency in Assembly Line Balancing Using a Genetic Algorithm

Anel, Juan Ignacio; Català, Pau; Serra, Moisès Serra i; Domenech, Bruno

doi:10.1016/j.orp.2022.100223

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…The mathematical developments to find the optimal solutions or the best solutions are applied to particle jamming algorithms (Şahin & Kellegöz, 2019;Sridevi & Chakkravarthy, 2021), genetic algorithms (Anel et al, 2022) or the ant colony algorithm (Lausch & Mönch, 2016;He et al, 2020); which, although they differ from each other, allow researchers to obtain the expected results. These solutions also provide more satisfactory results, demanding knowledge for their modeling and technologies that are not within the reach of a large part of the business sector, and which, if necessary, determine to optimize their productive capacities, establish if it is possible to respond to demand that imposes the market in which operations and programs are most effective in their productive flows.…”

Section: Research and Methodologymentioning

confidence: 99%

Optimization of heterogeneous capacities considering the profit margin per product

Pérez-Campdesuñer

Sánchez-Rodríguez

García-Vidal

et al. 2023

IJRBS

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This paper aims to present a proposal to improve this methodology for the analysis of heterogeneous capacities based on the profit margin per product. Which was structured in three moments: development of the proposal, deployment in a business context, and validation of the results through the application of a linear programming method. This proposal considers the five initial steps of the existing tools as a starting point, taking as a reference the normal time available for each homogeneous group and introducing modifications in the steps. The application of the methodology in the conditions of SMEs demonstrated its ability to generate results superior to those of traditional methods and similar to those obtained by specific linear programming techniques.

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Section: Research and Methodologymentioning

confidence: 99%

Optimization of heterogeneous capacities considering the profit margin per product

Pérez-Campdesuñer

Sánchez-Rodríguez

García-Vidal

et al. 2023

IJRBS

View full text Add to dashboard Cite

show abstract

“…Among the mathematical methods used in the search for optimal solutions, we can mention the ant colony algorithm (He, Peng, & Long, 2020;Lausch & Mönch, 2016). Genetic algorithms (Anel, Català, Serra, & Domenech, 2022) or particle swarm algorithms (Şahin & Kellegöz, 2019;Sridevi & Chakkravarthy, 2021) Although these have particularities that distinguish or differentiate them, they generally constitute methods that allow researchers to obtain the desired results. These methods generally assume an objective function that seeks to maximize cap acity or minimize cost or time.…”

Section: Literature Reviewmentioning

confidence: 99%

Unlocking the power of investment decision making with MATLAB: A cutting-edge method for optimizing capacities

Perez-Campdesuner,

Sanchez-Rodriguez,

Garcia-Vidal

et al. 2023

Nurture

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Purpose: The aim of this research was to present a method that would allow responding to both interests in a staggered and proportional way, in correspondence with existing financial availability. Design/Methodology/Approach: This research shows the results of the application of a methodological proposal programmed in MATLAB, which provided a solution to the described problem. Findings: The application was carried out in a small company, which has three fundamental products, and allowed to optimize the use of the available capital, increasing both the installed capacities and the potential demand for the products offered. Conclusion: It is possible to define an investment strategy that, based on the existence of an amount of financial availability, alternates the investment in the limiting capacity or the commercialization actions in correspondence with what is the limitation of the organization, which can be a limitation of capacity or market. This favors a systematic increase in the utility of the organization. Practical Implications: An analysis algorithm is developed that can serve as a guide for businessmen to design investment strategies aimed at increasing demand or capacity restrictions, as the case may be, based on financial availability and contributing to the systematic increase in the utility of the organization under study. Contribution to Literature: A method is presented that combines the analysis of capacity restrictions with those of demand restrictions, an aspect that is generally addressed in the literature independently.

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Effect of ergonomic aspects on single‐ and multiproduct assembly‐line balancing problems

Giridhar,

Panicker

2024

Hum Ftrs & Erg Mfg Svc

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Incorporating ergonomic considerations into an assembly‐line balancing problem (ALBP) enhances productivity and minimizes ergonomic concerns. The assembly process, characterized by repetitive motions and handling numerous components, can lead to worker overload. Consequently, the inclusion of ergonomic aspects results in an appropriate distribution of assembly operations and relative workloads. This study investigates a multi‐objective ALBP aimed at minimizing the number of workstations, overall skill level required, and variance in workers' energy expenditure across workstations. To address the ALBP while considering the ergonomic aspects, this study proposes an approach based on the non‐dominated sorting genetic algorithm II (NSGA‐II) and multi‐objective simulated annealing (MOSA) using Pareto optimality. A comparative analysis of the NSGA‐II and MOSA is conducted in single‐ and multiproduct production scenarios, and a computational study involving various factors is performed to identify the dominant algorithm. The computational analysis indicates that the runtime performance of MOSA is 73.287% better than that of NSGA‐II; therefore, MOSA outperforms NSGA‐II. This study aims at applying scientific knowledge concerning manufacturing ergonomics to assist manufacturing industries in enhancing their productivity.

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New Matrix Methodology for Algorithmic Transparency in Assembly Line Balancing Using a Genetic Algorithm

Cited by 3 publications

References 20 publications

Optimization of heterogeneous capacities considering the profit margin per product

Optimization of heterogeneous capacities considering the profit margin per product

Unlocking the power of investment decision making with MATLAB: A cutting-edge method for optimizing capacities

Effect of ergonomic aspects on single‐ and multiproduct assembly‐line balancing problems

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