Integrated pulp and paper mill planning and scheduling

Santos, Maristela Oliveira dos; Almada-Lobo, Bernardo

doi:10.1016/j.cie.2012.01.008

Cited by 60 publications

(43 citation statements)

References 22 publications

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“…Estas heurísticas têm sido aplicadas com sucesso em vários problemas de otimização [8]). Ambas heurísticas se baseiam na partição das variáveis inteiras do problema em conjuntos disjuntos.…”

Section: Parâmetros Adicionais D Jkunclassified

Uma Heurística para o Problema de Patrulhamento de Ambientes com múltiplos Agentes

Santos¹,

Massago²,

Romero³

et al. 2018

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Resumo. Neste trabalhoé proposto uma heurística para um problema de vigilância com múltiplos agentes em ambientes representados por meio de um grafo. Os nós do grafo representam os locais a serem visitados em cada ciclo. Um cicloé finalizado quando todas os locais são observados pelo menos uma vez por um agente. Deseja-se determinar as trajetórias dos agentes de modo que a duração de cada ciclo seja mínimo, que os agentes sejam incentivados a se movimentarem o máximo possível. Um modelo de programação inteira mista foi proposto bem como uma heurística baseada na decomposição do modelo. Alguns cenários foram gerados e usados para testar a abordagem heurística e os resultados obtidos mostram seu bom desempenho quando comparado a um solver comercial de otimização utilizado.Palavras-chave. Otimização inteira mista, Vigilância com múltiplos agentes, minimização ciclos, maximização visitas. IntroduçãoO termo patrulhamento ou vigilânciaé definido como a ação de percorrer uma região, em intervalos regulares, a fim de promover proteção ou supervisão da mesma. Dessa forma, para que estratégias de patrulhamento sejam eficazes, agentes (humanos ou artificiais) necessitam estabelecer uma coordenação adequada entre si, para que locais de um dado ambiente sejam visitados repetidas vezes ao longo do período de monitoramento [1]. Uma das formas de um sistema de vigilância trabalhar com um ambiente a ser observado implica no conhecimento prévio de seu ambiente, ou seja, informações de disposição e conectividade dos ambientes são fornecidas com antecedência. Por exemplo, considere um ambiente que pode ser representado por meio de um grafo de conectividade com suas 1

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Section: Parâmetros Adicionais D Jkunclassified

Uma Heurística para o Problema de Patrulhamento de Ambientes com múltiplos Agentes

Santos¹,

Massago²,

Romero³

et al. 2018

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

Self Cite

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“…The recent literature reviews by Almada-Lobo et al [3] and Copil et al [4] highlight an increasing interest in simultaneous lot-sizing and scheduling problems in many companies, resulting in researches motivated by industrial practical applications, such as glass container [5], animal nutrition [6], soft drink [7], wood floor [8], pulp and paper mill [9], food [10], automotive applications [11], supermarkets [12], and thin film transistor and liquid crystal display [13]. In these studies different models are used to represent lot-sizing and scheduling problems with sequence-dependent setups.…”

Section: Introductionmentioning

confidence: 99%

“…During 1 , the setup time contributes to the capacity consumption, contrary to 2 . Constraints (9) ensure that the production of only occurs in case the filling line is ready. Constraints (10) and (11) ensure that the filler must be prepared for a single item for each subperiod ∈ ( ∈ 1 ) and the number of preparations of the filler to Ω in every subperiod ∈ ( ∈ 2 ), respectively; in 2 the length of each subperiod is bigger than that of 1 .…”

mentioning

confidence: 99%

Alternative Mathematical Models and Solution Approaches for Lot‐Sizing and Scheduling Problems in the Brewery Industry: Analyzing Two Different Situations

Baldo

Morábito

Santos

et al. 2017

Mathematical Problems in Engineering

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This research proposes new approaches to deal with the production planning and scheduling problem in brewery facilities. Two real situations found in factories are addressed, which differ by considering (or not) the setup operations in tanks that provide liquid for bottling lines. Depending on the technology involved in the production process, the number of tank swaps is relevant (Case A) or it can be neglected (Case B). For both scenarios, new MIP (Mixed Integer Programming) formulations and heuristic solution methods based on these formulations are proposed. In order to evaluate the approach for Case A, we compare the results of a previous study with the results obtained in this paper. For the solution methods and the result analysis of Case B, we propose adaptations of Case A approaches yielding an alternative MIP formulation to represent it. Therefore, the main contributions of this article are twofold: (i) to propose alternative MIP models and solution methods for the problem in Case A, providing better results than previously reported, and (ii) to propose new MIP models and solution methods for Case B, analyzing and comparing the results and benefits for Case B considering the technology investment required.

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“…Various papers studying different planning problems associated with the pulp and paper industry can be found in the literature, such as using surplus steam for district healing [1,2], lot-sizing problems associated with paper machines [3], production problems integrating lot-sizing and cutting decisions in the paper machines [4,5] and integrated lot-sizing and scheduling problems [6,7]. As the focus of the present study is on problems coupling lot-sizing and scheduling decisions, some related papers which have tackled these integrated problems are described in more detail below.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, [6] studied the integrated problem in a Portuguese pulp and paper mill and proposed a MIP-based heuristic to solve it. The authors considered three sub-plants of the company: the pulp plant, the paper plant and the recovery plant.…”

Section: Introductionmentioning

confidence: 99%

Unequal individual genetic algorithm with intelligent diversification for the lot-scheduling problem in integrated mills using multiple-paper machines

Furlan

Almada-Lobo

Santos

et al. 2015

Computers & Operations Research

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This paper addresses the lot-sizing and scheduling problem of pulp and paper mills involving multiple paper machines. The underlying multi-stage integrated production process considers the following critical units: continuous digester, intermediate stocks of pulp and liquor, multiple paper machines and a recovery line to treat by-products. This work presents a mixed integer programming (MIP) model to represent the problem, as well as a solution approach based on a customized genetic algorithm (GA) with an embedded residual linear programming model. Some GA tools are explored, including literature and new operators, a novel diversification process and other features. In particular, the diversification process uses a new allele frequency measure to change between diversification and intensification procedures. Computational results show the effectiveness of the method to solve relatively large instances of the single paper machine problem when compared to other single paper machine solution methods found in the literature. For multiple paper machine settings, in most runs the GA solutions are better than those obtained for the MIP model using an optimization software.

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Integrated pulp and paper mill planning and scheduling

Cited by 60 publications

References 22 publications

Uma Heurística para o Problema de Patrulhamento de Ambientes com múltiplos Agentes

Uma Heurística para o Problema de Patrulhamento de Ambientes com múltiplos Agentes

Alternative Mathematical Models and Solution Approaches for Lot‐Sizing and Scheduling Problems in the Brewery Industry: Analyzing Two Different Situations

Unequal individual genetic algorithm with intelligent diversification for the lot-scheduling problem in integrated mills using multiple-paper machines

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