Estudo dos problemas de corte e empacotamento

Pós-graduação em Engenharia Elétrica - FEIS

A Aplicação de um modelo matemático na resolução de um problema de carregamento de paletes

Global competitiveness has been increased significantly in the last decade and, as consequence, companies are always looking for developing better processes in supply chain operations in order to maintain their competitive costs and keep themselves in the business. Logistics operations represent a large part of the product's final cost. Transportation can represent more than fifty percent of final cost sometimes. The solutions for cutting and packing problems consist in simple and low investment actions, as enhancing the arrangement of the transported load in order to decrease both material and room wastes. As per the presented reasons, the objective of this paper is to show and analyze a real application of a mathematical model to solve a manufacturer pallet-loading problem, comparing results from the model execution and the solution proposed by the company studied. This study will not only find the best arrangement to load pallets (which will optimize storage and transportation process), but also to check the effectiveness of existing modeling in the literature. For this study a computational package was used, which consists of a modeling language GAMS with the CPLEX optimization solver and two other existing software in the market, all of them indicating that an accurate mathematical model for solving this kind of problem in a two-dimensional approach is difficult to be found, in addition to a long execution time. However, the study and the software utilization indicate that the problem would be easily solved by heuristics in a shorter execution time

A Aplicação de um modelo matemático na resolução de um problema de carregamento de paletes

Global competitiveness has been increased significantly in the last decade and, as consequence, companies are always looking for developing better processes in supply chain operations in order to maintain their competitive costs and keep themselves in the business. Logistics operations represent a large part of the product's final cost. Transportation can represent more than fifty percent of final cost sometimes. The solutions for cutting and packing problems consist in simple and low investment actions, as enhancing the arrangement of the transported load in order to decrease both material and room wastes. As per the presented reasons, the objective of this paper is to show and analyze a real application of a mathematical model to solve a manufacturer pallet-loading problem, comparing results from the model execution and the solution proposed by the company studied. This study will not only find the best arrangement to load pallets (which will optimize storage and transportation process), but also to check the effectiveness of existing modeling in the literature. For this study a computational package was used, which consists of a modeling language GAMS with the CPLEX optimization solver and two other existing software in the market, all of them indicating that an accurate mathematical model for solving this kind of problem in a two-dimensional approach is difficult to be found, in addition to a long execution time. However, the study and the software utilization indicate that the problem would be easily solved by heuristics in a shorter execution time

Collision free region determination by modified polygonal Boolean operations

Cutting and packing problems are found in numerous industries such as garment, wood and shipbuilding. The collision free region concept is presented, as it represents all the translations possible for an item to be inserted into a container with already placed items. The often adopted nofit polygon concept and its analogous concept inner fit polygon are used to determine the collision free region. Boolean operations involving nofit polygons and inner fit polygons are used to determine the collision free region. New robust non-regularized Boolean operations algorithm is proposed to determine the collision free region. The algorithm is capable of dealing with degenerated boundaries. This capability is important because degenerated boundaries often represent local optimal placements. A parallelized version of the algorithm is also proposed and tests are performed in order to determine the execution times of both the serial and parallel versions of the algorithm.

Solução rasterizada para o problema de empacotamento de fita irregular utilizando a Montanha Voronoi.

O empacotamento irregular de fita é um grupo de problemas na área de corte e empacotamento, cuja aplicação é observada nas indústrias têxtil, moveleira e construção naval. O problema consiste em definir uma configuração de itens irregulares de modo que o comprimento do contêiner retangular que contém o leiaute seja minimizado. A solução deve ser válida, isto é, não deve haver sobreposição entre os itens, que não devem extrapolar as paredes do contêiner. Devido a aspectos práticos, são admitidas até quatro orientações para o item. O volume de material desperdiçado está diretamente relacionado à qualidade do leiaute obtido e, por este motivo, uma solução eficiente pressupõe uma vantagem econômica e resulta em um menor impacto ambiental. O objetivo deste trabalho consiste na geração automática de leiautes de modo a obter níveis de compactação e tempo de processamento compatíveis com outras soluções na literatura. A fim de atingir este objetivo, são realizadas duas propostas de solução. A primeira consiste no posicionamento sequencial dos itens de modo a maximizar a ocorrência de posições de encaixe, que estão relacionadas à restrição de movimento de um item no leiaute. Em linhas gerais, várias sequências de posicionamentos são exploradas com o objetivo de encontrar a solução mais compacta. Na segunda abordagem, que consiste na principal proposta deste trabalho, métodos rasterizados são aplicados para movimentar itens de acordo com uma grade de posicionamento, admitindo sobreposição. O método é baseado na estratégia de minimização de sobreposição, cujo objetivo é a eliminação da sobreposição em um contêiner fechado. Ambos os algoritmos foram testados utilizando o mesmo conjunto de problemas de referência da literatura. Foi verificado que a primeira estratégia não foi capaz de obter soluções satisfatórias, apesar de fornecer informações importantes sobre as propriedades das posições de encaixe. Por outro lado, a segunda abordagem obteve resultados competitivos. O desempenho do algoritmo também foi compatível com outras soluções, inclusive em casos nos quais o volume de dados era alto. Ademais, como trabalho futuro, o algoritmo pode ser estendido de modo a possibilitar a entrada de itens de geometria genérica, o que pode se tornar o grande diferencial da proposta.

Procedure di Programmazione Dinamica per Determinare le K Migliori Soluzioni del Knapsack Problem 0-1 e dello Shortest Path Problem

In questa tesi viene trattata la problematica di determinare le migliori K soluzioni per due problemi di ottimizzazione, il Knapsack Problem 0-1 e lo Shortest Path Problem. Tali soluzioni possono essere impiegate all'interno di metodi di column generation per la risoluzione di problemi reali, ad esempio Bin Packing Problems e problemi di scheduling di veicoli ed equipaggi. Sono stati implementati, per verificarne sperimentalmente le prestazioni, nuovi algoritmi di programmazione dinamica, sviluppati nell’ambito di un programma di ricerca. Inizialmente, per entrambi i problemi, è stato descritto un algoritmo che determinasse le migliori K soluzioni per ogni possibile sottoproblema; partendo da uno zaino con capacità nulla, nel caso del Knapsack Problem 0-1, e dalla determinazione di un cammino dal vertice sorgente in se stesso per lo Shortest Path Problem, l’algoritmo determina le migliori soluzioni di sottoproblemi via via sempre più grandi, utilizzando le soluzioni costruite per gli stati precedenti, fino a ottenere le migliori soluzioni del problema globale. Successivamente, è stato definito un algoritmo basato su un approccio di ricorsione backward; in questo caso si utilizza una funzione ricorsiva che, chiamata a partire dallo stato corrispondente al problema globale, viene richiamata solo sugli stati intermedi strettamente necessari, e per ognuno di essi non vengono determinate soluzioni superflue.

Meat through the microscope; applications of chemistry and the biological sciences to some problems of the meat packing industry,

"Lithoprinted."

A Study of Ordered Gene Problems Featuring DNA Error Correction and DNA Fragment Assembly with a Variety of Heuristics, Genetic Algorithm Variations, and Dynamic Representations

Ordered gene problems are a very common classification of optimization problems. Because of their popularity countless algorithms have been developed in an attempt to find high quality solutions to the problems. It is also common to see many different types of problems reduced to ordered gene style problems as there are many popular heuristics and metaheuristics for them due to their popularity. Multiple ordered gene problems are studied, namely, the travelling salesman problem, bin packing problem, and graph colouring problem. In addition, two bioinformatics problems not traditionally seen as ordered gene problems are studied: DNA error correction and DNA fragment assembly. These problems are studied with multiple variations and combinations of heuristics and metaheuristics with two distinct types or representations. The majority of the algorithms are built around the Recentering- Restarting Genetic Algorithm. The algorithm variations were successful on all problems studied, and particularly for the two bioinformatics problems. For DNA Error Correction multiple cases were found with 100% of the codes being corrected. The algorithm variations were also able to beat all other state-of-the-art DNA Fragment Assemblers on 13 out of 16 benchmark problem instances.

Orthogonal packing of identical rectangles within isotropic convex regions

A mixed integer continuous nonlinear model and a solution method for the problem of orthogonally packing identical rectangles within an arbitrary convex region are introduced in the present work. The convex region is assumed to be made of an isotropic material in such a way that arbitrary rotations of the items, preserving the orthogonality constraint, are allowed. The solution method is based on a combination of branch and bound and active-set strategies for bound-constrained minimization of smooth functions. Numerical results show the reliability of the presented approach. (C) 2010 Elsevier Ltd. All rights reserved.

An algorithm for the strip packing problem using collision free region and exact fitting placement

The irregular shape packing problem is approached. The container has a fixed width and an open dimension to be minimized. The proposed algorithm constructively creates the solution using an ordered list of items and a placement heuristic. Simulated annealing is the adopted metaheuristic to solve the optimization problem. A two-level algorithm is used to minimize the open dimension of the container. To ensure feasible layouts, the concept of collision free region is used. A collision free region represents all possible translations for an item to be placed and may be degenerated. For a moving item, the proposed placement heuristic detects the presence of exact fits (when the item is fully constrained by its surroundings) and exact slides (when the item position is constrained in all but one direction). The relevance of these positions is analyzed and a new placement heuristic is proposed. Computational comparisons on benchmark problems show that the proposed algorithm generated highly competitive solutions. Moreover, our algorithm updated some best known results. (C) 2012 Elsevier Ltd. All rights reserved.

Algorithms and Models For Combinatorial Optimization Problems

In this thesis we present some combinatorial optimization problems, suggest models and algorithms for their effective solution. For each problem,we give its description, followed by a short literature review, provide methods to solve it and, finally, present computational results and comparisons with previous works to show the effectiveness of the proposed approaches. The considered problems are: the Generalized Traveling Salesman Problem (GTSP), the Bin Packing Problem with Conflicts(BPPC) and the Fair Layout Problem (FLOP).

Two-Dimensional Bin Packing Problem with Guillotine Restrictions

This thesis, after presenting recent advances obtained for the two-dimensional bin packing problem, focuses on the case where guillotine restrictions are imposed. A mathematical characterization of non-guillotine patterns is provided and the relation between the solution value of the two-dimensional problem with guillotine restrictions and the two-dimensional problem unrestricted is being studied from a worst-case perspective. Finally it presents a new heuristic algorithm, for the two-dimensional problem with guillotine restrictions, based on partial enumeration, and computationally evaluates its performance on a large set of instances from the literature. Computational experiments show that the algorithm is able to produce proven optimal solutions for a large number of problems, and gives a tight approximation of the optimum in the remaining cases.

Measuring and improving production efficiency of paint filling and packing line

Tutkittu yritys on suomalainen maaleja ja lakkoja kansainvälisesti valmistava ja myyvä toimija. Yrityksessä otettiin vuonna 2010 käyttöön uudet tuotannon ja toimitusketjun tavoitteet ja suunnitelmat ja tämä tutkimus on osa tuota kokonaisvaltaista kehittämissuuntaa. Tutkimuksessa käsitellään tuotannon ja kunnossapidon tehokkuuden parantamis- ja mittaustyökalu OEE:tä ja tuotevaihtoaikojen pienentämiseen tarkoitettua SMED -työkalua. Työn teoriaosuus perustuu lähinnä akateemisiin julkaisuihin, mutta myös haastatteluihin, kirjoihin, internet sivuihin ja yhteen vuosikertomukseen. Empiriaosuudessa OEE:n käyttöönoton ongelmia ja onnistumista tutkittiin toistettavalla käyttäjäkyselyllä. OEE:n potentiaalia ja käyttöönottoa tutkittiin myös tarkastelemalla tuotanto- ja käytettävyysdataa, jota oli kerätty tuotantolinjalta. SMED:iä tutkittiin siihen perustuvan tietokoneohjelman avulla. SMED:iä tutkittiin teoreettisella tasolla, eikä sitä implementoitu vielä käytäntöön. Tutkimustuloksien mukaan OEE ja SMED sopivat hyvin esimerkkiyritykselle ja niissä on paljon potentiaalia. OEE ei ainoastaan paljasta käytettävyyshäviöiden määrää, mutta myös niiden rakenteen. OEE -tulosten avulla yritys voi suunnata rajalliset tuotannon ja kunnossapidon parantamisen resurssit oikeisiin paikkoihin. Työssä käsiteltävä tuotantolinja ei tuottanut mitään 56 % kaikesta suunnitellusta tuotantoajasta huhtikuussa 2016. Linjan pysähdyksistä ajallisesti 44 % johtui vaihto-, aloitus- tai lopetustöistä. Tuloksista voidaan päätellä, että käytettävyyshäviöt ovat vakava ongelma yrityksen tuotannontehokkuudessa ja vaihtotöiden vähentäminen on tärkeä kehityskohde. Vaihtoaikaa voitaisiin vähentää ~15 % yksinkertaisilla ja halvoilla SMED:illä löydetyillä muutoksilla työjärjestyksessä ja työkaluissa. Parannus olisi vielä suurempi kattavimmilla muutoksilla. SMED:in suurin potentiaali ei välttämättä ole vaihtoaikojen lyhentämisessä vaan niiden standardisoinnissa.

The three-dimensional single-bin-size bin packing problem: combining metaheuristic and machine learning approaches

The Three-Dimensional Single-Bin-Size Bin Packing Problem is one of the most studied problem in the Cutting & Packing category. From a strictly mathematical point of view, it consists of packing a finite set of strongly heterogeneous “small” boxes, called items, into a finite set of identical “large” rectangles, called bins, minimizing the unused volume and requiring that the items are packed without overlapping. The great interest is mainly due to the number of real-world applications in which it arises, such as pallet and container loading, cutting objects out of a piece of material and packaging design. Depending on these real-world applications, more objective functions and more practical constraints could be needed. After a brief discussion about the real-world applications of the problem and a exhaustive literature review, the design of a two-stage algorithm to solve the aforementioned problem is presented. The algorithm must be able to provide the spatial coordinates of the placed boxes vertices and also the optimal boxes input sequence, while guaranteeing geometric, stability, fragility constraints and a reduced computational time. Due to NP-hard complexity of this type of combinatorial problems, a fusion of metaheuristic and machine learning techniques is adopted. In particular, a hybrid genetic algorithm coupled with a feedforward neural network is used. In the first stage, a rich dataset is created starting from a set of real input instances provided by an industrial company and the feedforward neural network is trained on it. After its training, given a new input instance, the hybrid genetic algorithm is able to run using the neural network output as input parameter vector, providing as output the optimal solution. The effectiveness of the proposed works is confirmed via several experimental tests.

Impact Of Pharmacist Interventions On Drug-related Problems And Laboratory Markers In Outpatients With Human Immunodeficiency Virus Infection.

Substantial complexity has been introduced into treatment regimens for patients with human immunodeficiency virus (HIV) infection. Many drug-related problems (DRPs) are detected in these patients, such as low adherence, therapeutic inefficacy, and safety issues. We evaluated the impact of pharmacist interventions on CD4+ T-lymphocyte count, HIV viral load, and DRPs in patients with HIV infection. In this 18-month prospective controlled study, 90 outpatients were selected by convenience sampling from the Hospital Dia-University of Campinas Teaching Hospital (Brazil). Forty-five patients comprised the pharmacist intervention group and 45 the control group; all patients had HIV infection with or without acquired immunodeficiency syndrome. Pharmaceutical appointments were conducted based on the Pharmacotherapy Workup method, although DRPs and pharmacist intervention classifications were modified for applicability to institutional service limitations and research requirements. Pharmacist interventions were performed immediately after detection of DRPs. The main outcome measures were DRPs, CD4+ T-lymphocyte count, and HIV viral load. After pharmacist intervention, DRPs decreased from 5.2 (95% confidence interval [CI] =4.1-6.2) to 4.2 (95% CI =3.3-5.1) per patient (P=0.043). A total of 122 pharmacist interventions were proposed, with an average of 2.7 interventions per patient. All the pharmacist interventions were accepted by physicians, and among patients, the interventions were well accepted during the appointments, but compliance with the interventions was not measured. A statistically significant increase in CD4+ T-lymphocyte count in the intervention group was found (260.7 cells/mm(3) [95% CI =175.8-345.6] to 312.0 cells/mm(3) [95% CI =23.5-40.6], P=0.015), which was not observed in the control group. There was no statistical difference between the groups regarding HIV viral load. This study suggests that pharmacist interventions in patients with HIV infection can cause an increase in CD4+ T-lymphocyte counts and a decrease in DRPs, demonstrating the importance of an optimal pharmaceutical care plan.