Optimization Methods for Lot-Sizing Problem in an Automated Foundry

Duda, Jerzy; Stawowy, A.

doi:10.2478/amm-2013-0088

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…Stawowy e Duda (2012) Duda e Stawowy (2013) propuseram métodos e/ou modelos para o problema de planejamento da produção em fundições de pequeno porte.…”

Section: Introductionunclassified

Dimensionamento de lotes em fundições de pequeno porte com múltiplos fornos

Toledo¹,

Camargo²,

Oliveira³

et al. 2015

Anais Do Congresso Nacional De Matemática Aplicada À Indústria

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Resumo. O planejamento da produção em fundições de pequeno porteé especialmente difícil devidoà variedade de ligas e itens que são produzidos. Este problema pode ser resumido a determinar quais itens serão produzidos em cada período do horizonte de planejamento e, consequentemente, quais ligas devem ser fundidas para garantir essa produção. Essas decisões estão diretamente relacionadas, pois cada itemé vazado a partir de uma liga específica. Logo, os itens a serem produzidos num dado período dependem das ligas que forem fundidas. Em cada período, o número de fusõesé limitado e o volume de liga fundida correspondenteà capacidade do forno utilizado. Na literatura, esse problema considerando apenas um forno para a produção foi tratado utilizando métodos exatos e heurísticos. Embora na prática seja relevante considerar no processo de planejamento mais de um tipo de forno, poucos trabalhos incluem esta questão. Planejar a produção considerando vários fornosé especialmente importante por questões de economia de energia elétrica e, consequentemente, redução dos custos de produção. Neste trabalho, propomos um modelo inteiro misto para o problema de dimensionamento de lotes inspirado numa fundição de pequeno porte do Estado de São Paulo. A fundição dispõe de dois fornos que não podem ser utilizados simultaneamente. Testes computacionais foram conduzidos com o objetivo de comparar o planejamento integrado dos fornos com soluções da literatura para problemas em que apenas um fornoé tratado.Palavras-chave: planejamento de produção; otimização inteira; fundição; múltiplos fornos INTRODUÇÃONeste trabalho, abordamos o problema de planejamento de produção em fundições de pequeno porte. De forma geral, um plano de produção deve especificar quais ligas serão fundidas e quais peças serão vazadas a partir destas ligas. A definição de um plano de produção eficienteé particularmente difícil devidoà grande variedade de ligas e itens que são produzidos.As fundições de pequeno porte têm um importante papel na economia brasileira, pois pertencem a cadeia produtiva de indústrias de diferentes setores, como, por exemplo, automobilístico e agrícola. Além disso, são responsáveis por muitos empregos diretos e indiretos.Devido a sua importância econômica e ao desafio científico que o problema de planejamento de sua produção representa, vários autores estudaram o problema. Stawowy e Duda (2012) apresentam uma revisão de artigos que abordam o problema.

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“…Stawowy e Duda (2012) Duda e Stawowy (2013) propuseram métodos e/ou modelos para o problema de planejamento da produção em fundições de pequeno porte.…”

Section: Introductionunclassified

Dimensionamento de lotes em fundições de pequeno porte com múltiplos fornos

Toledo¹,

Camargo²,

Oliveira³

et al. 2015

Anais Do Congresso Nacional De Matemática Aplicada À Indústria

View full text Add to dashboard Cite

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“…The producing iron castings problem is the motivation for present work in foundry enterprise. In recent years, experts and scholars have put many researches' focus on the scheduling optimization algorithm and proposed some effective methods or models, such as multiobjective evolutionary algorithms [9] (DLP, Deterministic Linear Programming [10], ACO, Ant Colony Optimization [11], ABC, Artificial Bee Colony [12], AIA, Artificial Immune Algorithm [13], UGF, Universal Generation Function [14], and MIP, Mixed-Integer Programming [15]) and decision support optimization and simulation (SLP, System Layout Planning [16], MIND, Method for Analysis of Industrial Energy Systems [17], M&FS, Mass and Fuzzy Sets [18], SDST, Spreadsheet Decision Support Tool [19], SDSM, Scheduling Decision Support Model [20], TOFPS, Two-phase Order Fulfillment Planning Structure [21], and ERP&NN, ERP System including Neural Network [22]).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The minimum value (min ) of total cost of production planning is obtained by (14). Because the total amount of all orders ( ) is fixed, in order to standardize calculation process of IGA, the maximum profit rate of all orders (max Pr) is defined as the objective of IGA which is shown as (15):…”

Section: Fitness Evaluation Fitness Function Of Genetic Algorithmmentioning

confidence: 99%

A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint

Guo

Liu

et al. 2017

Mathematical Problems in Engineering

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The mode of production in the modern manufacturing enterprise mainly prefers to MTO (Make-to-Order); how to reasonably arrange the production plan has become a very common and urgent problem for enterprises’ managers to improve inner production reformation in the competitive market environment. In this paper, a mathematical model of production planning is proposed to maximize the profit with capacity constraint. Four kinds of cost factors (material cost, process cost, delay cost, and facility occupy cost) are considered in the proposed model. Different factors not only result in different profit but also result in different satisfaction degrees of customers. Particularly, the delay cost and facility occupy cost cannot reach the minimum at the same time; the two objectives are interactional. This paper presents a mathematical model based on the actual production process of a foundry flow shop. An improved genetic algorithm (IGA) is proposed to solve the biobjective problem of the model. Also, the gene encoding and decoding, the definition of fitness function, and genetic operators have been illustrated. In addition, the proposed algorithm is used to solve the production planning problem of a foundry flow shop in a casting enterprise. And comparisons with other recently published algorithms show the efficiency and effectiveness of the proposed algorithm.

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“…Reasonable operational planning is the core of reducing production costs [3,4] and can be divided into: workshop scheduling that is the core of manufacturing execution system, production lotsizing planning implemented by enterprise resource planning, and various combinations of these [5]. In most specific production scenarios, these problems are NP-hard problems, which have been proved by previous studies [6,7]. Moreover, rising energy prices are driving manufacturing companies to reduce their production energy consumption [8].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Genetic Algorithm Based on Fuzzy Reasoning for the Multilevel Capacitated Lot-Sizing Problem with Energy Consumption in Synchronizer Production

et al. 2022

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The multilevel capacitated lot-sizing problem (MLCLSP) is a vital theoretical problem of production planning in discrete manufacturing. An improved algorithm based on the genetic algorithm (GA) is proposed to solve the MLCLSP. Based on the solution results, the distribution of energy consumption in a synchronous production case is analyzed. In the related literature, the GA has become a much-discussed topic in solving these kinds of problems. Although the standard GA can make up for the defects of the traditional algorithm, it will lead to the problems of unstable solution results and easy local convergence. For these reasons, this research presents an adaptive genetic algorithm based on fuzzy theory (fuzzy-GA) to solve the MLCLSP. Firstly, the solving process of the MLCLSP with the fuzzy-GA is described in detail, where algorithms for key technologies such as the capacity constraint algorithm and the algorithm of solving fitness value are developed. Secondly, the auto-encoding of decision variables for MLCLSPs is studied; within this, the decision variables of whether to produce or not are encoded into a hierarchical structure based on the bill of material; combined with external demand, the decision variables of lot-sizing are constructed. Thirdly, the adaptive optimization process of parameters of the GA for the MLCLSP based on fuzzy theory is expounded, in which membership function, fuzzy rule, and defuzzification of the MLCLSP is mainly presented. Experimental studies using the processed dataset collected from a synchronizer manufacturer have demonstrated the merits of the proposed approach, in which the energy consumption distribution of the optimized production plan is given. The optimal lot-sizing is closer to the average value of the optimal value compared with the standard GA, which indicates that the proposed fuzzy-GA approach has better convergence and stability.

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Optimization Methods for Lot-Sizing Problem in an Automated Foundry

Cited by 4 publications

References 7 publications

Dimensionamento de lotes em fundições de pequeno porte com múltiplos fornos

Dimensionamento de lotes em fundições de pequeno porte com múltiplos fornos

A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint

Adaptive Genetic Algorithm Based on Fuzzy Reasoning for the Multilevel Capacitated Lot-Sizing Problem with Energy Consumption in Synchronizer Production

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