An ACO Algorithm to Solve an Extended Cutting Stock Problem for Scrap Minimization in a Bar Mill

Díaz, Diego; Valledor, Pablo; Areces, Paula; Rodil, Jorge; Suárez, Montserrat

doi:10.1007/978-3-319-09952-1_2

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…For example, the company AntOptima (www.antoptima.com) plays an important role in promoting the real-world application of ACO. Furthermore, the company Arcelor-Mittal uses ACO algorithms to solve several of the optimization problems arising in their production sites [55,80]. In real-world applications, features such as time-varying data, multiple objectives or the availability of stochastic information about events or data are rather common.…”

Section: Discussionmentioning

confidence: 99%

An Introduction to Ant Colony Optimization

Dorigo

Socha

2018

Handbook of Approximation Algorithms and Metaheuristics, Second Edition

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Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the pheromone trail laying and following behavior of some ant species. Artificial ants in ACO are stochastic solution construction procedures that build candidate solutions for the problem instance under concern by exploiting (artificial) pheromone information that is adapted based on the ants' search experience and possibly available heuristic information. Since the proposal of Ant System, the first ACO algorithm, many significant research results have been obtained. These contributions focused on the development of high performing algorithmic variants, the development of a generic algorithmic framework for ACO algorithm, successful applications of ACO algorithms to a wide range of computationally hard problems, and the theoretical understanding of important properties of ACO algorithms. This chapter reviews these developments and gives an overview of recent research trends in ACO.

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Section: Discussionmentioning

confidence: 99%

An Introduction to Ant Colony Optimization

Dorigo

Socha

2018

Handbook of Approximation Algorithms and Metaheuristics, Second Edition

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“…The success of ACO is also witnessed by a number of industrial applications. For example, AntOptima (www.antoptima.com) is a small company using the ACO methodology for tackling industrial problems in distribution and production management, while ArcelorMittal is using ACO algorithms in various areas relevant to steel production to improve operative production performance [25,44]. ACO is also a central topic of journals and conferences specializing in the area of swarm intelligence such as the ANTS conference series started in 1998 (http://iridia.ulb.ac.be/ants/) and the journal "Swarm Intelligence."…”

Section: Discussionmentioning

confidence: 99%

Ant Colony Optimization: A Component-Wise Overview

López-Ibáñez¹,

Stützle²,

Dorigo³

2016

Handbook of Heuristics

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The indirect communication and foraging behavior of certain species of ants have inspired a number of optimization algorithms for NP-hard problems. These algorithms are nowadays collectively known as the ant colony optimization (ACO) metaheuristic. This chapter gives an overview of the history of ACO, explains in detail its algorithmic components, and summarizes its key characteristics. In addition, the chapter introduces a software framework that unifies the implementation of these ACO algorithms for two example problems, the traveling salesman problem and the quadratic assignment problem. By configuring the parameters of the framework, one can combine features from various ACO algorithms in novel ways. Examples on how to find a good configuration automatically are given in the chapter. The chapter closes with a review of combinations of ACO with other techniques and extensions of the ACO metaheuristic to other problem classes.

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“…Muchos de estos algoritmos se han utilizado para resolver el Problema de patrones de corte, entre los cuales se destaca Tabu Search (TS), Greedy Randomized Adaptive Search Procedure (GRASP) [42] , Algoritmos genéticos [43][44][45][46] y Ant Colony optimization (ACO) [47,48], entre otros algoritmos evolucionarios [2], [2,[49][50][51][52].Según [6] desarrolló una tipología de enfoques de solución teniendo en cuenta el tipo de problema, para lo cual los dividió en dos categorías: orientados a los objetos o ítems, y los orientados a los patrones tal como se muestra en la tabla 2.…”

Section: Metaheurísticasunclassified

El Problema de patrones de corte, clasificación y enfoques/Cutting stock problem, classification and approaches

2017

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RESUMENEl Problema de patrones es de gran importancia para empresas manufactureras que involucran el proceso de cortar grandes rollos de algún material y pasarlos a rollos más pequeños de diferentes anchos, considerando el efecto que este tienen sobre los inventarios de producto en proceso y materias primas. Una apropiada gestión de este problema no solo genera benéficos económicos, sino que también genera impactos sostenibles, en la medida que busca un equilibrio entre el costo de inventario y los desperdicios del proceso. Conscientes de la importancia de este problema en este trabajo se presenta inicialmente una introducción de lo que significa en complejidad la solución de un problema de este tipo en una empresa. Luego se enuncian sus antecedentes mediante los trabajos más importantes encontrados en la literatura, destacando algunos trabajos colombianos. Posteriormente, se aborda la clasificación del problema y se aportan sugerencias de otros aspectos a tener en cuenta en el problema. Finalmente se enmarcan los cuatro enfoques de solución más comunes dando ideas para investigaciones futura esperando con esto contribuir al desarrollo del tema.Palabras clave: Planeación del inventario; Proceso de cortado; Modelación matemática; Planeación de operaciones; Minimización de desperdicios. El problema de patrones de corte o cutting stock problem. ABSTRACTThe Cutting stock problem is of great importance for manufacturing companies that involving the process of cutting large rolls of some material into small strips of different widths, considering the effect this has on product inventories in process and raw materials. Proper management of this problem not only generates beneficial economic but also generates sustainable impacts, to the extent that seeks a balance between the cost of inventory and process waste. This paper first presents an overview of what complexity means in solving a problem of this type in a company. His background is set out with the most important works in the literature, highlighting some Colombian jobs. Then, we present classification problem and suggestions from other aspects are provided to consider when addressed cutting stock problem. Finally are framed the four most common approaches to solution giving ideas for future research, hoping thereby contribute to the development of the topic.

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An ACO Algorithm to Solve an Extended Cutting Stock Problem for Scrap Minimization in a Bar Mill

Cited by 7 publications

References 11 publications

An Introduction to Ant Colony Optimization

An Introduction to Ant Colony Optimization

Ant Colony Optimization: A Component-Wise Overview

El Problema de patrones de corte, clasificación y enfoques/Cutting stock problem, classification and approaches

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