Yes / Prior studies show the impact of various facets of individual characteristics in driving a firm’s entrepreneurial orientation (EO). The present study complements this line of research by deriving insights from the conservation of resources (COR) theory to examine the effects of resource-induced coping heuristics (acquiring, protecting, and developing resources) on EO. Additionally, it investigates the underlying conditions influencing these relationships. Data were collected from new ventures in two developing countries (Ghana, N=204, and Ethiopia, N=214). Utilizing the moderated hierarchical regression analysis, the results show that the three dimensions of resource-induced coping heuristics positively relate to EO and these relationships are amplified when environmental dynamism is high. These findings provide a nuanced understanding of the relationships among the different types of resource-induced coping heuristics and EO. In this way, the study extends the boundaries of the resource-induced coping heuristics, EO, and broader entrepreneurship literature.

The research is a study of the efficiency and robustness of genetic algorithm to instances of both discrete and continuous global optimization problems. We developed genetic algorithm based heuristics to find the global minimum to problem instances considered. In the discrete category, we considered two instances of real-world space allocation problems that arose from an academic environment in a developing country. These are the university timetabling problem and hostel space allocation problem. University timetabling represents a difficult optimization problem and finding a high quality solution is a challenging task. Many approaches, based on instances from developed countries, have been reported in the literature. However, most developing countries are yet to appreciate the deployment of heuristics and metaheuristics in handling the timetabling problem. We therefore worked on an instance from a university in Nigeria to show the feasibility and efficiency of heuristic method to the timetabling problem. We adopt a simplified bottom up approach in which timetable are build around departments. Thus a small portion of real data was used for experimental testing purposes. As with similar baseline studies in literature, we employ genetic algorithm to solve this instance and show that efficient solutions that meet stated constraints can be obtained with the metaheuristics. This thesis further focuses on an instance of university space allocation problem, namely the hostel space allocation problem. This is a new instance of the space allocation problems that has not been studied by metaheuristic researchers to the best of our knowledge. The problem aims at the allocation of categories of students into available hostel space. This must be done without violating any hard constraints but satisfying as many soft constraints as possible and ensuring optimum space utilization. We identified some issues in the problem that helped to adapt metaheuristic approach to solve it. The problem is multi-stage and highly constrained. We first highlight an initial investigation based on genetic algorithm adapted to find a good solution within the search space of the hostel space allocation problem. Some ideas are introduced to increase the overall performance of initial results based on instance of the problem from our case study. Computational results obtained are reported to demonstrate the effectiveness of the solution approaches employed. Sensitivity analysis was conducted on the genetic algorithm for the two SAPs considered to determine the best parameter values that consistently give good solutions. We noted that the genetic algorithms perform well specially, when repair strategies are incorporated. This thesis pioneers the application of metaheuristics to solve the hostel space allocation problem. It provides a baseline study of the problem based on genetic algorithms with associated test data sets. We report the best known results for the test instances. It is a known fact that many real-life problems are formulated as global optimization problems with continuous variables. On the continuous global optimization category therefore, we focus on improving the efficiency and reliability of real coded genetic algorithm for solving unconstrained global optimization, mainly through hybridization with exploratory features. Hybridization has widely been recognized as one of the most attractive approach to solving unconstrained global optimization. Literatures have shown that hybridization helps component heuristics to taking advantage of their individual strengths while avoiding their weaknesses. We therefore derived three modified forms of real coded genetic algorithm by hybridizing the standard real-coded genetic algorithm with pattern search and vector projection. These are combined to form three new algorithms namely, RCGA-PS, RCGA-P, and RCGA-PS-P. The hybridization strategy used and results obtained are reported and compared with the standard real-coded genetic algorithm. Experimental studies show that all the modified algorithms perform better than the original algorithm.

Este trabalho teve como objetivo a avaliação de um software comercial de roteirização de veículos. Tal software, o Delivery, se propõe a ser uma ferramenta de apoio à decisão na escolha da rotina operacional de coleta e/ou distribuição física de produtos, através da criação de roteiros alternativos, o que possibilita analisar a viabilidade de implantação da rotina operacional. A proposta original consistia em desenvolver uma metodologia para testar e avaliar a qualidade das soluções geradas pelo algoritmo deste sistema. O trabalho foi conduzido através de uma pesquisa bibliográfica dos problemas clássicos de roteirização e programação de veículos, abordando suas classificações, estratégias e técnicas de solução. Um estudo em empresas que utilizam procedimentos sistemáticos de roteirização foi realizado, com a intenção de caracterizar o cenário em que se desenvolve a atividade de distribuição física. Neste estudo foi possível identificar as características mais relevantes para sistemas comerciais de roteirização de veículos, bem como caracterizar os software utilizados pelas empresas em questão. Finalmente, realizou-se uma análise empírica comparativa entre os software Delivery e TransCAD através da aplicação de problemas testes encontrados na literatura que representam algumas classes do problema de roteirização de veículos, além da aplicação de um caso real. Resultados demonstraram que a heurística do software TransCAD apresenta melhor desempenho que a do software Delivery. / The aim of this work is to evaluate a commercial computer program for vehicle routing. The software, named Delivery, has been designed to be a decision-support tool for planning goods collection and/or distribution. Its capacity for creating several alternative routes is very useful in the analysis of possible operational schemes before their actual implementation. A methodology for testing and evaluating the quality of the solution generated by the algorithm has been applied in this work, after a comprehensive literature review of the traditional vehicle routing and scheduling problems, their classification, and solution techniques and strategies. A field study in some companies that actually use a similar tool for routing their fleets has been carried out, in order to better understand how the activity is performed in real world conditions. The most important characteristics of commercial vehicle routing systems has been also identified in the field study, as well as the software used by the studied companies. Finally, a comparative empirical analysis with the software Delivery and TransCAD has been carried out. In order to compare them, test problems available in the literature, that correspond to some of the most common vehicle routing problems, and a real case application were employed. The results have shown that the heuristic of TransCAD had a better performance than the one used in Delivery.

Este trabalho teve como objetivo a avaliação de um software comercial de roteirização de veículos. Tal software, o Delivery, se propõe a ser uma ferramenta de apoio à decisão na escolha da rotina operacional de coleta e/ou distribuição física de produtos, através da criação de roteiros alternativos, o que possibilita analisar a viabilidade de implantação da rotina operacional. A proposta original consistia em desenvolver uma metodologia para testar e avaliar a qualidade das soluções geradas pelo algoritmo deste sistema. O trabalho foi conduzido através de uma pesquisa bibliográfica dos problemas clássicos de roteirização e programação de veículos, abordando suas classificações, estratégias e técnicas de solução. Um estudo em empresas que utilizam procedimentos sistemáticos de roteirização foi realizado, com a intenção de caracterizar o cenário em que se desenvolve a atividade de distribuição física. Neste estudo foi possível identificar as características mais relevantes para sistemas comerciais de roteirização de veículos, bem como caracterizar os software utilizados pelas empresas em questão. Finalmente, realizou-se uma análise empírica comparativa entre os software Delivery e TransCAD através da aplicação de problemas testes encontrados na literatura que representam algumas classes do problema de roteirização de veículos, além da aplicação de um caso real. Resultados demonstraram que a heurística do software TransCAD apresenta melhor desempenho que a do software Delivery. / The aim of this work is to evaluate a commercial computer program for vehicle routing. The software, named Delivery, has been designed to be a decision-support tool for planning goods collection and/or distribution. Its capacity for creating several alternative routes is very useful in the analysis of possible operational schemes before their actual implementation. A methodology for testing and evaluating the quality of the solution generated by the algorithm has been applied in this work, after a comprehensive literature review of the traditional vehicle routing and scheduling problems, their classification, and solution techniques and strategies. A field study in some companies that actually use a similar tool for routing their fleets has been carried out, in order to better understand how the activity is performed in real world conditions. The most important characteristics of commercial vehicle routing systems has been also identified in the field study, as well as the software used by the studied companies. Finally, a comparative empirical analysis with the software Delivery and TransCAD has been carried out. In order to compare them, test problems available in the literature, that correspond to some of the most common vehicle routing problems, and a real case application were employed. The results have shown that the heuristic of TransCAD had a better performance than the one used in Delivery.

This thesis covers a product development process carried out in collaboration with Ericsson –Enclosure & Power and their development of Radio Base Stations (RBS). As Ericsson expands into new markets, the different customer demands on their support systems increases in number and variation. In order to improve their business structure and still provide a wide array of product solutions, they are currently developing a new modular product family. Today numerous methods for product modularization exist, but there is a lack of experience of using such methods at Ericsson – Enclosure & Power. This thesis is an exploration of what methods could be suitable to use in this context, and how to implement them in a beneficial way. The object of study is the Battery Base Unit (BBU), a mounting base for RBS cabinets that contains a compartment for backup batteries. A methodology is suggested for developing this product in a way that secures a proper modular structure. Part of the methodology consists of standard product development methods such as Quality Function Deployment (QFD), concept selection and prototyping. The other part consist of the modularization methods Function Structure Heuristics and Design Structure Matrix (DSM), that are employed first on functional level before developing concepts and secondly on component-based level while detailing the final concept. The thesis describes how these implementations have been made, how the product have been developed from idea to prototype and the resulting product modularity. The final design is evaluated against the product specification and the benefits and drawbacks of using a formalized modularization process for product development at Ericsson – Enclosure & Power are discussed. / Detta arbete handlar om den produktutveckling som utförts i samarbete med Ericsson –Enclosure & Power och deras utveckling av kabinett för radiobasstationer (RBS). Ericssons expansion på nya marknader ökar mängden krav på deras olika supportsystem. För att kunna vidareutveckla sin verksamhet och samtidigt erbjuda ett stort antal produktlösningar utvecklar de för närvarande en ny modulbaserad produktfamilj. Idag finns ett flertal metoder för produktmodularisering men man saknar erfarenhet av att arbeta med sådana metoder på Ericsson– Enclosure & Power. Detta arbete undersöker vilka metoder som är lämpliga att använda i detta sammanhang, och hur man på bästa sätt ska implementera dem. Objektet för denna studie är Batteribasenheten (BBUn) som är ett fundament för montering av RBS kabinettet med ett utrymme för reservbatterier. Ett övergripande tillvägagångssätt föreslås för att säkerställa att utvecklingen av denna produkt inkluderar en bra modulär uppbyggnad. Delvis består tillvägagångssättet av vanliga produktutvecklingsmetoder såsom Quality Function Deployment (QFD), koncepturval och prototyper. I övrigt består det i modulariseringsmetoderna Function Structure Heuristics och Design Structure Matrix (DSM) som används först på funktionsnivå innan konceptgenereringsfasen och därefter på komponentnivå under detaljutvecklingen av det slutliga konceptet. Detta arbete beskriver hur dessa metoder har implementerats, hur produktenhar utvecklats från idé till prototyp samt den resulterande produktmodulariteten. Den slutliga utformningen utvärderas mot den angivna kravspecificeringen och fördelarna och nackdelarna med att använda en formaliserad metod för produktutveckling på Ericsson – Enclosure & Power diskuteras.

Internet of Things (IoT) devices are increasingly being used everywhere, from the factory to the hospital to the house to the car. IoT devices typically have limited processing resources, so they must rely on cloud servers to accomplish their tasks. Thus, many obstacles need to be overcome while offloading tasks to the cloud. In reality, an excessive amount of data must be transferred between IoT devices and the cloud, resulting in issues such as slow processing, high latency, and limited bandwidth. As a result, the concept of edge computing was developed to place compute nodes closer to the end users. Because of the limited resources available at the edge nodes, when it comes to meeting the needs of IoT devices, tasks must be optimally scheduled between IoT devices, edge nodes, and cloud nodes.  In this thesis, we model the offloading problem in an edge cloud infrastructure as a Mixed-Integer Linear Programming (MILP) problem and look for efficient optimization techniques to tackle it, aiming to minimize the total delay of the system after completing all tasks of all services requested by all users. To accomplish this, we use the exact approaches like simplex to find a solution to the MILP problem. Due to the fact that precise techniques, such as simplex, require a large number of processing resources and a considerable amount of time to solve the problem, we propose several heuristics and meta-heuristics methods to solve the problem and use the simplex findings as a benchmark to evaluate these methods. Heuristics are quick and generate workable solutions in certain circumstances, but they cannot guarantee optimal results. Meta-heuristics are slower than heuristics and may require more computations, but they are more generic and capable of handling a variety of problems. In order to solve this issue, we propose two meta-heuristic approaches, one based on a genetic algorithm and the other on simulated annealing. Compared to heuristics algorithms, the genetic algorithm-based method yields a more accurate solution, but it requires more time and resources to solve the MILP, while the simulated annealing-based method is a better fit for the problem since it produces more accurate solutions in less time than the genetics-based method. / Internet of Things (IoT) devices are increasingly being used everywhere. IoT devices typically have limited processing resources, so they must rely on cloud servers to accomplish their tasks. In reality, an excessive amount of data must be transferred between IoT devices and the cloud, resulting in issues such as slow processing, high latency, and limited bandwidth. As a result, the concept of edge computing was developed to place compute nodes closer to the end users. Because of the limited resources available at the edge nodes, when it comes to meeting the needs of IoT devices, tasks must be optimally scheduled between IoT devices, edge nodes, and cloud nodes.  In this thesis, the offloading problem in an edge cloud infrastructure is modeled as a Mixed-Integer Linear Programming (MILP) problem, and efficient optimization techniques seeking to minimize the total delay of the system are employed to address it. To accomplish this, the exact approaches are used to find a solution to the MILP problem. Due to the fact that precise techniques require a large number of processing resources and a considerable amount of time to solve the problem, several heuristics and meta-heuristics methods are proposed. Heuristics are quick and generate workable solutions in certain circumstances, but they cannot guarantee optimal results while meta-heuristics are slower than heuristics and may require more computations, but they are more generic and capable of handling a variety of problems.

The emergence of 5G alongside the distributed computing paradigm called Edge computing has prompted a tremendous change in the industry through the opportunity for reducing network latency and energy consumption and providing scalability. Edge computing extends the capabilities of users’ resource-constrained devices by placing data centers at the edge of the network. Computation offloading enables edge computing by allowing the migration of users’ tasks to edge servers. Deciding whether it is beneficial for a mobile device to offload a task and on which server to offload, while environmental variables, such as availability, load, network quality, etc., are changing dynamically, is a challenging problem that requires careful consideration to achieve better performance. This project focuses on proposing lightweight and efficient algorithms to take offloading decisions from the mobile device perspective to benefit the user. Subsequently, heuristic techniques have been examined as a way to find quick but sub-optimal solutions. These techniques have been combined with a Multi-Armed Bandit algorithm, called Discounted Upper Confidence Bound (DUCB) to take optimal decisions quickly. The findings indicate that these heuristic approaches cannot handle the dynamicity of the problem and the DUCB provides the ability to adapt to changing circumstances without having to keep adding extra parameters. Overall, the DUCB algorithm performs better in terms of local energy consumption and can improve service time most of the times. / Utvecklingen av 5G har skett parallellt med det distribuerade beräkningsparadigm som går under namnet Edge Computing. Lokala datacenter placerade på kanten av nätverket kan reducera nätverkslatensen och energiförbrukningen för applikationer. Exempelvis kan användarenheter med begränsade resurser ges utökande möjligheter genom avlastning av beräkningsintensiva uppgifter. Avlastningen sker genom att migrera de beräkningsintensiva uppgifterna till en dator i datacentret på kanten. Det är dock inte säkert att det alltid lönar sig att avlasta en beräkningsintensiv uppgift från en enhet till kanten. Detta måste avgöras från fall till fall. Att avgöra om och när det lönar sig är ett svårt problem då förutsättningar som tillgänglighet, last, nätverkskvalitét, etcetera hela tiden varierar. Fokus i detta projekt är att identifiera enkla och effektiva algoritmer som kan avgöra om det lönar sig för en användare att avlasta en beräkningsintensiv uppgift från en mobil enhet till kanten. Heuristiska tekniker har utvärderats som en möjlig väg att snabbt hitta lösningar även om de råkar vara suboptimala. Dessa tekniker har kombinerats med en flerarmad banditalgoritm (Multi-Armed Bandit), kallad Discounted Upper Confidence Bound (DUCB), för att ta optimala beslut snabbt. Resultaten indikerar att dessa heuristiska tekniker inte kan hantera de dynamiska förändringar som hela tiden sker samtidigt som DUCB kan anpassa sig till dessa förändrade omständigheter utan att man måste addera extra parametrar. Sammantaget, ger DUCM-algoritmen bättre resultat när det gäller lokal energikonsumtion och kan i de flesta fallen förbättra tiden för tjänsten.

本研究的目的為研究國中九年級學生在學習機率單元前後，對於機率概念的了解與代表性偏誤、可利用性偏誤Kahneman＆Tversky(1974)）及結果取向判斷偏誤(Konold1989)的異同。主要採量的分析，以自訂的問卷評量工具對受試者進行筆試。研究之樣本為學過國小簡單機率的國中九年級學生，問卷實施的方式為筆試，研究過程設計了前測、後測兩份試卷，並在施測前進行預試來評估試題信度、效度。前測問卷施測目的在探討學生在教學前利用常識、直觀來解題所可能造成的機率偏誤。教學過後也進行後測問卷的施測，並利用前後兩次施測的結果，探討國中生在教學前後機率判斷偏誤上的差異性。本研究之對象為中學九年級學生，共148位學生來進行施測，研究者依學生數學分組教學之成績，分為高分群、中間群、低分群，依據性別和分群兩個變項來進行分析。分析結果發現： 1.性別變項無顯著差異，故教學過程中不用特別考慮性別差異。 2.分群分析結果如下： (1)結果取向 在一次投擲問題中，前、後測問卷分析結果發現，中、高分群前後測整體表現皆無偏誤的比例較低分群來的少。 (2)代表性偏誤 在代表性偏誤中的正時近效應與負時近效應的問題中，低分群在前、後測仍犯有偏誤比中、高分群前後測都犯有偏誤的比例來的高。而改變樣本空間問題中，中、高分群在前、後測皆沒有偏誤的比比例較低分群高。複合樣本問題中探討代表性偏誤，低分群在前、後測仍然有偏誤的比例較中、高分群前、後測犯有偏誤高。 (3)可利用性偏誤 三群在前、後測的綜合表現並無顯著差異。 / The study aims to explore the differences of judgmental heuristic and biases on representativeness, availability (Kahneman &Tversky, 1974) and outcome approach (Konold, 1989) in terms of comprehension of probability concepts by ninth graders before and after studying the subject. The results are based on a quantitative analysis of the data collected from two sets of paper-and-pencil self-designed questionnaires. Pre-test questionnaire is meant to explore students’ potential probability biases when they work out the problems based on their previous knowledge and intuition prior to any instruction, while post-test questionnaire is conducted after instruction. The subjects in our experiment are composed of one hundred and forty-eight ninth graders who have only learned some basic probability concepts in primary school, and are classified into high-, mid- and low-scorer groups based on their previous academic performance. The findings suggest that: 1. Gender effect is not significantly different, so there is no need to pay attention to the gender difference in teaching process. 2. The results of analyses for different groups are listed in what follows. (1) Outcome approach: In the problem of tossing a coin, the results of pre-test and post-test indicate that the proportion of subjects who are without biases is higher in mid- and high-scorers than that of low-scorers. (2) Representativeness bias: In the problem of positive recency effect and negative recency effect, the proportion of committing biases is higher in low-scorers than that of mid- and high-scorers in both pre- and post-tests. In the problem of changes in sample spaces, the proportion of lack of biases is higher in mid- and high-scorers than that of low-scorers. In the composite-event problem that deals with representative biases, the proportion of committing biases among low-scorers is higher than that of mid- and high-scorers in both pre- and post-tests. (3) Availability bias: There is no significant difference in the overall performance of pre- and post-tests among the three groups.

[pt] Nesta tese são propostos modelos e algoritmos aproximados para o Problema da Árvore Geradora de Custo Mínimo com Restrição de Diâmetro (AGMD). Este problema modela tipicamente aplicações em projetos de redes de computadores onde todos os vértices devem comunicar-se entre si a um custo mínimo, garantindo um certo nível de serviço. Os modelos propostos por Achuthan e Caccetta para o AGMD são reforçados através da introdução de restrições válidas. Uma relaxação lagrangeana é proposta para o modelo de multifluxo básico de Gouveia e Magnanti. Essa relaxação é utilizada para o desenvolvimento de heurísticas lagrangeanas. Adaptações são realizadas nas heurísticas construtivas propostas por Deo e Abdalla, e por Raidl e Julstrom. São propostas ainda quatro estratégias de busca local, uma heurística do tipo GRASP e outra híbrida. São obtidos limites superiores a menos de 2% do ótimo para as classes de instâncias usadas nos trabalhos de Gouveia e Magnanti, e de Santos, Lucena e Ribeiro. Além disto, obteve-se os melhores resultados conhecidos até o presente momento para 11 instâncias de grafos completos usadas por Raidl, Julstrom e Gruber. / [en] In this work, models and approximation algorithms to solve the Diameter Constrained Minimum Spanning Tree Problem (AGMD) are proposed. This problem typically models network design applications where all vertices must communicate with each other at a minimum cost, while meeting a given quality requirement. The formulations proposed by Achuthan and Caccetta are strengthened with valid inequalities. A lagrangean relaxation is proposed for the multicommodity flow model developed by Gouveia and Magnanti. Adaptations are made in the constructive heuristics proposed by Deo and Abdalla and by Raidl and Julstrom. Four local search procedures, a GRASP algorithm and a hybrid heuristic are proposed. Upper bounds within 2% of the optimal solution values are obtained for the two classes of instances used by Gouveia and Magnanti and by Santos, Lucena and Ribeiro. Moreover, stronger upper bounds are reported for 11 instances in complete graphs used by Raidl, Julstrom and Gruber

Esta tese de doutorado apresenta modelos matemáticos de problemas de dimensionamento de lotes para planejamento da produção na indústria de embalagens de vidro, que são essenciais em qualquer cadeia de produção, pois são responsáveis por proteger e conservar os produtos (alimentos e bebidas). Na literatura científica são raros os trabalhos que abordam estudos sobre problemas combinados de dimensionamento de lotes e planejamentos da produção em indústrias de embalagens de vidro. Com a finalidade de preencher esta lacuna, a presente tese tem por objetivo propor modelos inéditos e métodos de resolução aplicáveis em problemas nas indústrias de embalagens de vidro. Dessa forma, propõem-se dois modelos baseados em problemas reais para a construção ou reforma de forno(s), denominados de Problema de Instalação de um Novo Forno e Problema de Instalação de Múltiplos Fornos, que verificam a capacidade de fusão e as configurações das máquinas instaladas. Outros dois modelos são desenvolvidos a partir de estudos de casos referentes ao planejamento e ao controle da produção de ampolas de garrafas térmicas. No primeiro estudo, considera-se o máximo da produção líquida e no segundo, minimiza-se os set-up, sendo que em ambos os casos a realidade de uma fábrica é refletida. A complexidade desses modelos contribui para o uso de métodos heurísticos e meta-heurísticos como técnicas para resolução dos mesmos. No entanto, considera-se também a avaliação da associação desses métodos ao uso de programação matemática. Para isso, modelos matemáticos são propostos dentro do contexto das indústrias consideradas. Desta forma, uma heurística de Filtro Guloso e as meta-heurísticas como o Algoritmo Genético Simples, o Algoritmo Genético Multi-Populacional e o Algoritmo Genético Modificado são utilizados na determinação das variáveis inteiras presentes nos modelos matemáticos. Além disso, utiliza-se um método exato, por meio da ferramenta CPLEX, para determinar as variáveis contínuas. Os estudos são conduzidos a partir de dados fornecidos por indústrias localizadas no Brasil e em Portugal. Portanto, os resultados colaboram com o estado da arte nessa área de pesquisa e com o processo de fabricação industrial de embalagens de vidro. / This doctoral dissertation presents mathematical models of lot-sizing problems for production planning in the glass containers industry, which are essential in any production chain, as they are responsible for protecting and conserving products (food and beverages). In the scientific literature, studies addressing combined problems of batch sizing and production planning in glass containers industries are rare. In order to fill this gap, this thesis aims to propose novel models and resolution methods applicable to problems in the glass containers industry. Thus, we propose two models based on real problems for the construction or remodelling of the furnace (s), called New Furnace Installation Problem and Multiple Furnace Installation Problem, which verify fusibility and configurations of installed machines. We developed two other models from case studies regarding the planning and control of the production of thermos vials. In the first study, we consider the maximum net production; in the second, we minimize the set-up. Both cases reflect the reality of a factory. The complexity of these models contributes to the use of heuristic and metaheuristic methods as techniques for their resolution. However, we also consider the evaluation of the association of these methods with the use of mathematical programming. For this, we propose mathematical models within the context of the considered industries. Thus, a Greedy Filter heuristic and metaheuristics such as the Simple Genetic Algorithm, the Multi-Population Genetic Algorithm and the Modified Genetic Algorithm are used to determine the integer variables present in mathematical models. Besides, we use an exact method from CPLEX tool to determine continuous variables. The studies are conducted from data provided by industries located in Brazil and Portugal. Therefore, the results collaborate with state of the art in this research area and with the industrial glass containers manufacturing process.