Abstract Assembly lines are a production mechanism that has historically presented economic and quality benefits in organizations. However, different problems arise during their execution, among them, the issue of balancing assembly lines with multi-manned stations. This situation occurs more frequently in industrial organizations that manufacture products of medium and large dimensions, compared to a single worker per workstation model. Despite this, we find a greater tendency to study the second case in the literature. In contrast, few studies refer to the first, in addition, exhaustive search methods such as linear programming have encountered barriers due to computational complexity, so research on this problem has focused on using heuristics looking for more efficient algorithms in order to solve it. Therefore, the present work proposes a genetic algorithm that, to our knowledge, has not been used in the search to minimize the number of workers and the number of workstations for the balancing model of assembly lines with multi-manned stations. In addition, a new cost function is proposed that weights the number of workstations and workers, punishing solutions with high idle times to avoid their selection. The results of the proposed algorithm are evaluated by comparing test instances presented in the literature. The algorithm is available at <https://github.com/juanseck/GAMmALB>.

Resumen Las líneas de ensamble son un mecanismo de producción que históricamente ha presentado beneficios económicos y de calidad en las organizaciones; sin embargo, diferentes problemas se presentan durante su ejecución. Entre estos destaca el problema del modelo de balanceo de líneas de ensamble con estaciones multi-tripuladas, el cual suele presentarse con mayor frecuencia en las organizaciones industriales que fabrican productos de dimensiones medianas y grandes, en comparación con el modelo de un solo tripulante por estación de trabajo; a pesar de ello, en la literatura encontramos una mayor tendencia a estudiar el segundo caso. Pocos estudios hacen referencia al primero. Adicionalmente, los métodos de búsqueda exhaustiva como los de programación lineal han encontrado barreras debido a la complejidad computacional, por lo cual las investigaciones sobre este problema se han centrado en utilizar heurísticos para su solución, en la búsqueda de algoritmos que sean cada vez más eficientes. Por lo anterior, el presente trabajo propone un algoritmo genético que en nuestro conocimiento no se ha utilizado en la búsqueda por minimizar el número de trabajadores y el número de estaciones de trabajo para el modelo de balanceo de líneas de ensamble con estaciones multi-tripuladas. Además, se propone una nueva función de costos la cual pondera el número de estaciones de trabajo y trabajadores, castigando soluciones con tiempos muertos altos para evitar su selección. Los resultados del algoritmo propuesto son evaluados mediante la comparación de instancias de prueba presentadas en la literatura. El algoritmo está disponible en <https://github.com/juanseck/GAMmALB>.

ABSTRACT Improving efficiency in the application of irrigation water, due to its scarcity, is a matter of concern to all decision-makers in the country, since it is not possible to continue managing the precious liquid with current guidelines. Studying the efficiency of irrigation in Cuban agriculture as a combination of resources will allow us to know where the application of water will be of greater benefit, always in combination with other resources used in the production process. In this context, the use of non-parametric techniques such as data envelopment analysis is convenient, given its flexibility and ability to handle the productive characteristics of entities. The analysis of irrigation by means of DEA, will allow to evaluate where the management of the water is carried out in a more efficient way.

RESUMEN Mejorar la eficiencia en la aplicación del agua de riego, debido a su escasez, es una cuestión que preocupa a todos los decisores del país pues no es posible seguir gestionando el preciado líquido con las pautas actuales. Estudiar la eficiencia de riego en la agricultura cubana como una combinación de recursos va a permitir conocer donde la aplicación del agua va a suponer un mayor beneficio, siempre en combinación con otros recursos empleados en el proceso de producción. En este contexto, resulta conveniente el empleo de técnicas no paramétricas como el análisis envolvente de datos, dado su flexibilidad y capacidad de manejar las particularidades productivas de las entidades. El análisis de los regadíos mediante DEA, permitirá evaluar donde la gestión del agua se realiza de una forma más eficiente.

Abstract This paper introduces the Julia programming language as a dynamic, cost-effective, and efficient framework for implementing structural analysis packages. To achieve this, the finite element method was implemented for plane frames addressing the elastic instability problem through the Finite Element Method (FEM). Julia is a language open source, multiplatform, high-level and high-performance for technical and scientific computing, its compiler allows you to achieve speeds comparable to languages such as C and FORTRAN, but with more productive development dynamics due to its programming flexibility. Benchmarks between Julia and MATLAB are employed to discuss the processing costs, the programming techniques and paradigms used for computational performance. The results demonstrate that Julia performed the same analysis as the language used for comparison in 88.40% of the time, in addition to the fact that in loops comparisons case it reached 41.7% of the time for iteration, confirming its significant potential as a development tool of computational packages for structural analysis and scientific computing in general. dynamic costeffective, costeffective cost effective, effective cost-effective this FEM. FEM . (FEM) source multiplatform highlevel high level highperformance performance FORTRAN flexibility costs 8840 88 40 88.40 417 41 7 41.7 iteration general (FEM 884 8 4 88.4 41. 88.

ABSTRACT We study a class of integer bilevel problems, the so-called Integer Linear Multiplicative Bilevel Problem, ILMBP, where the constraints are linear and both the upper level problem and the lower level problem are integer linear multiplicative problems. We assume that the k -linear factors of the upper level problem and the l -linear factors of the lower level problem to be non-negative. In this paper, we propose an algorithm based on branch-and-cut method for solving the Integer Linear Multiplicative Bilevel Problem. First, the continuous upper level linear multiplicative problem is solved, then the optimal integer solution obtained is tested for the optimality of the main problem by solving the lower level linear multiplicative problem. If this solution is not optimal for the problem ILMBP, a cut is added to the upper level problem and a new best integer solution is determined. The integer solution is generated by the branching process well known in the branch and bound procedure. Following, the presentation and validation of the algorithm, an example is provided to better visualize the algorithm. problems socalled so called Problem ILMBP nonnegative. nonnegative non negative. negative non-negative paper branchandcut First solved determined procedure Following

Abstract In this study, an integer linear programming model is proposed to support the Production Planning, Scheduling and Control sector of a printing company. The model considers two objective functions to deal with the problem, the first is to minimize the costs with electric energy consumption and the second is to minimize the machine operating time. Both objectives are related to the assignment to different sets of printing and finishing machines for the manufacture of the ordered items. Operating constraints at the factory are considered, such as the setup time limits, how the machine is operated, the types of printed item, the production capacity and the demand. In addition, a heuristic was developed to support the production schedule, allowing adjustments in the different production shifts but respecting the assignments obtained using the mathematical model. Computational tests were performed with a set of data provided by a printing company located in the state of São Paulo. study Planning problem items considered limits operated item demand addition schedule Paulo

Resumo Neste trabalho, é proposto um modelo matemático de programação linear inteira para auxiliar o setor de Planejamento, Programação e Controle da Produção de uma indústria gráfica. O modelo considera duas funções objetivos para tratar o problema, a primeira para minimizar os custos com o consumo de energia elétrica e, a segunda, para minimizar o tempo operacional das máquinas, ambas relativas à designação e utilização de conjuntos distintos de máquinas de impressão e de acabamento para a confecção dos itens demandados. São consideradas restrições operacionais da indústria, tais como, os limites de tempo de setup e de operação das máquinas, tipos de item impresso, capacidade de produção e atendimento de demanda. Além disso, uma heurística foi desenvolvida para auxiliar a programação da produção, permitindo ajustes nos respectivos turnos de produção da indústria, mas respeitando a designação obtida pela resolução do modelo matemático. Testes computacionais foram realizados com um conjunto de dados fornecidos por uma indústria gráfica situada no interior do estado de São Paulo. trabalho Planejamento problema segunda demandados como impresso demanda disso Paulo

This review aims to provide a comprehensive evaluation of the dynamics of the double pendulum, with a particular emphasis on its chaotic behavior. It examines the complicated and unpredictable behavior of the double pendulum. It highlights the pedagogical value of the double pendulum as it bridges concepts across physics, mathematics, and computer science, providing a tangible demonstration of chaotic dynamics. Numerical methods, such as the 4th-order Runge-Kutta method, estimate solutions to the autonomous Hamiltonian equations that govern a system. We simulate the motion of a double pendulum, enabling the visualization of intricate trajectories and the analysis of emerging patterns with the Python and Fortran programming languages. We discuss the importance of Poincaré’s maps and the Lyapunov exponents in characterizing and quantifying the rate at which trajectories diverge in phase space to elucidate the chaotic nature of the system. The educational significance of the double pendulum is emphasized in teaching key concepts in Classical Mechanics, Differential Calculus, Linear Algebra, and Numerical Methods for solving ordinary differential equations (ODEs). We also explore the interdisciplinary teaching opportunities presented by the double pendulum. physics mathematics science methods 4thorder thorder 4th order th RungeKutta Runge Kutta method system languages Poincarés Poincaré s Mechanics Calculus Algebra ODEs. ODEs . (ODEs) (ODEs

Abstract Since the open-pit precedence-constrained production scheduling problem is an NP-hard problem, solving it is always a challenging task, especially from a long-term perspective because a mineral deposit containing millions of blocks would require several million precedence arcs as constraints, making the solution time grow exponentially and making a direct approach unfeasible. Therefore, different strategies have been employed since the 1960s to reduce the size of this problem, such as determining the ultimate pit limit, subdividing it into phases, segmenting the production scheduling problem into long-, mid-, and short-term plans, as well as aggregating blocks into clusters, thus significantly reducing the number of precedence arcs. Different modeling and clustering strategies have already been employed in an attempt to reduce the size of the mine sequencing problem, such as layer modeling, re-blocking, bench-phase clustering, or polygon (mining cut) clustering based on a similarity function. The mining cut clustering problem has been solved lately by machine learning and heuristics techniques, and this approach can also introduce operational constraints to the mine sequencing problem, such as equipment size, minimum pit width, and preferential mining direction. In this study, we propose a mining cut clustering model based on Mixed Integer Linear Programming (MILP). Then we solve it by an exact approach and by Constraint Programming (CP), analyzing the strengths and weaknesses of the Constraint Optimization Problem (COP) and Constraint Satisfaction Problem (CSP) techniques. Numerical experiments were carried out on the Bench 15 of the Newmanl dataset, demonstrating the superiority of the COP approach. openpit open precedenceconstrained constrained NPhard NP hard task longterm long term unfeasible Therefore s limit phases long, , long- mid, mid mid- shortterm short plans clusters reblocking, reblocking re blocking, blocking re-blocking benchphase bench phase function techniques width direction study MILP. MILP . (MILP) CP, CP (CP) (COP CSP (CSP 1 dataset (MILP (CP

ABSTRACT The prospects for reducing organic load in water basins must be evaluated considering the self-purification capacities of the water bodies into which the raw or treated effluent will be discharged. The aim of this work was to evaluate the reduction of the organic load contribution to the Poti River, a watercourse that crosses the city of Teresina, Piauí, Brazil, considering different conditions for the final disposal of domestic sewage. To estimate the levels of reduction of the organic load contribution, the Water Quality Model Qual-UFMG and Nonlinear Programming were used in a combined manner. Three scenarios of final effluent disposal were modeled. For the appropriation of the reductions in organic load contributions, two different optimization models were used, models that incorporated restrictions based on the environmental quality standards indicated by the Brazilian Environment Council (CONAMA) Resolutions No. 357/2005 and 430/2011. The results indicated that the estimated effort for removal of organic load based on the optimization model that does not employ an equity measure among discharges was lower, regardless of the scenario analyzed. Additionally, in the simulation scenarios in which the quality standards for effluent were not considered, the efforts for removing organic load were lower, regardless of the optimization model used. selfpurification self purification discharged River Teresina Piauí Brazil sewage QualUFMG Qual UFMG manner modeled contributions CONAMA (CONAMA No 3572005 357 2005 357/200 4302011 430 2011 430/2011 lower analyzed Additionally considered 357200 35 200 357/20 430201 43 201 430/201 35720 3 20 357/2 43020 4 430/20 3572 2 357/ 4302 430/2 430/

RESUMO A perspectiva de redução de aporte orgânico em bacias hidrográficas deve ser avaliada com base na capacidade de autodepuração dos corpos d’água nos quais serão despejados os efluentes brutos ou tratados. O objetivo do presente trabalho foi a avaliação da redução do aporte de carga orgânica afluente ao rio Poti, curso d’água que corta o município de Teresina, Piauí, Brasil, considerando-se diferentes condições de disposição final de esgotos domésticos. Para a estimativa de níveis de redução do aporte de carga orgânica foram empregados, de maneira combinada, o modelo de qualidade de água Qual-UFMG e a Programação Não Linear. Foram modelados três cenários de disposição final de efluentes. Para a apropriação das reduções dos aportes de carga orgânica, dois diferentes modelos de otimização foram utilizados, modelos que incorporaram restrições baseadas nos padrões de qualidade ambiental estabelecidos pelas Resoluções do Conselho Nacional do Meio Ambiente (CONAMA) n° 357/2005 e n° 430/2011. Os resultados demonstraram que o esforço de remoção de carga orgânica estimado pelo modelo de otimização que não emprega medida de equidade entre lançamentos foi menor, independentemente do cenário de simulação analisado. Adicionalmente, nos cenários de simulação em que não foram considerados os padrões de qualidade para os efluentes, os esforços de remoção de carga orgânica foram menores, independentemente do modelo de otimização empregado. dágua d tratados Poti Teresina Piauí Brasil considerandose considerando se domésticos empregados combinada QualUFMG Qual UFMG Linear utilizados CONAMA (CONAMA n 3572005 357 2005 357/200 4302011 430 2011 430/2011 menor analisado Adicionalmente menores empregado 357200 35 200 357/20 430201 43 201 430/201 35720 3 20 357/2 43020 4 430/20 3572 2 357/ 4302 430/2 430/

Abstract Energy sources, like hydro and wind power, present uncertain nature, characteristic that affects the electric power systems operation planning. Such factors require using methodologies capable to handle these uncertainties in interconnected hydro-thermal-wind power systems operation. This work proposes a computational model for the day-ahead unit commitment problem for interconnected hydro-thermal-wind power systems, considering the uncertainties related to wind power, water inflow, and energy demand, employing the Robust Optimization (RO). The optimization model consists in a three-level mixed integer linear programming problem, which is resolved using a two-stage decomposition approach, solved using the column-and-constraint generation algorithm. The model is validated using the 30 nodes IEEE and the 33 nodes Brazilian test system. The model proposed proved to have an operating cost proportional to the level of uncertainty and the methodology employed provides a preventive view of what may occur during the hydro-thermal-wind systems operation, allowing the central system operator to take certain actions in order to ensure reliable operating conditions. In addition, the model allowed the identification of important aspects related to computational costs, such as the verification that constraints that couple the problem in time and space significantly impact the simulation times of the problem. sources nature planning hydrothermalwind thermal dayahead day ahead inflow demand RO. RO . (RO) threelevel three twostage two stage approach columnandconstraint column constraint algorithm 3 conditions addition costs (RO

ABSTRACT This paper proposes an integrated control model that enables the pesticide use according to the prey density and the insertion of the natural enemy, the predators, by fuzzy linear programming.The fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) is one of the main resistant pests of corn, which can cause damage to the productivity up to 34%. The control is strictly chemical. enemy predators programmingThe programming Lepidoptera (Lepidoptera Noctuidae corn 34 34% chemical 3

ABSTRACT In this work, a model based on the BVNS (Basic Variable Neighborhood Search) solution technique is proposed to solve the problem of restoring electrical energy distribution systems, considering in the model the participation of customers who are part of a demand response program and that can contribute to the restoration process allowing a number of its loads to be disconnected by the utility. The mathematical model consists of minimizing the cost of energy not distributed in the system due to unrestored sections, added to the remuneration costs of customers who are part of the demand response program, subject to the technical, physical and operational restrictions of distribution networks. This is a mixed integer nonlinear programming problem in which solution proposals are obtained through the BVNS algorithm. The neighborhood structure of the BVNS algorithm is based on the Node-Depth Representation technique. In this restoration process, carried out by the BVNS algorithm, for each solution evaluated, if any restriction is violated, a Genetic Algorithm is processed to perform load cuts in the sections with customers who are part of the demand response program. To test the efficiency of the proposed model, test results on a 53-section distribution system are presented. work Basic Search systems utility technical networks NodeDepth Node Depth evaluated violated 53section section 53 presented 5

RESUMO Neste trabalho é proposto um modelo baseado na técnica de solução BVNS (Basic Variable Neighborhood Search) para solucionar o problema de restauração de sistemas de distribuição de energia elétrica, considerando no modelo a participação de clientes que fazem parte de um programa de resposta à demanda e que podem contribuir no processo de restauração permitindo que uma quantidade de suas cargas seja desligada pela concessionária. O modelo matemático consiste em minimizar o custo de energia não distribuída no sistema devido às seções não restauradas, somado aos custos de remuneração dos clientes que fazem parte do programa de resposta à demanda, sujeito às restrições técnicas, físicas e operacionais de redes de distribuição. Trata-se de um problema de programação não-linear inteira mista em que as propostas de soluções são obtidas através do algoritmo BVNS. A estrutura de vizinhança do algoritmo BVNS é baseada na técnica Representação Nó-profundidade. Nesse processo de restauração, realizado pelo algoritmo BVNS, para cada solução avaliada, caso alguma restrição seja violada, um Algoritmo Genético é processado para realizar cortes de cargas nas seções com clientes que fazem parte do programa de resposta à demanda. Para testar a eficiência do modelo proposto, apresentam-se resultados de testes em um sistema de distribuição de 53 seções. Basic Search elétrica concessionária restauradas técnicas Tratase Trata se nãolinear linear Nóprofundidade. Nóprofundidade Nó profundidade. profundidade Nó-profundidade avaliada violada apresentamse apresentam 5

Resumo Este artigo estima os impactos potenciais de um eventual desabastecimento do diesel sobre a economia brasileira. Para tanto, utiliza-se um modelo insumo-produto integrado a procedimentos de programação linear a fim de simular efeitos diretos, indiretos e induzidos sobre a renda e a geração de empregos. Os resultados revelam implicações socioeconômicas expressivas para curtos períodos (10 dias) de restrição na disponibilidade e apontam para perdas potenciais significativas devido às características da estrutura produtiva, em particular relativas ao setor de transporte. Mais especificamente, os resultados mostram um impacto potencial de redução de R$ 76,28 bilhões do PIB brasileiro, o equivalente a 1,5% do PIB de 2015. As estimativas mostram queda potencial que poderia atingir 1,8 milhões de postos de trabalho. As evidências obtidas contribuem para orientar políticas públicas de planejamento energético e chamam atenção para a necessidade de formação de estoques estratégicos de diesel. brasileira tanto utilizase utiliza se insumoproduto insumo produto diretos empregos 10 (1 dias produtiva transporte especificamente R 7628 76 28 76,2 brasileiro 15 1 5 1,5 2015 18 8 1, trabalho ( 762 7 2 76, 201 20

Abstract This paper estimates the potential impacts of a possible diesel shortage on the Brazilian economy. To this end, an input-output model integrated with linear programming procedures is used to simulate direct, indirect, and induced effects on income and job creation. The results reveal significant socioeconomic implications for short periods (10 days) of restricted availability and point to significant potential losses due to the characteristics of the productive structure, particularly those relating to the transport sector. More specifically, the results show a potential impact of reducing Brazilian GDP by R$76.28 billion, equivalent to 1.5% of 2015 GDP. Estimates show a potential drop that could reach 1.8 million jobs. The evidence obtained contributes to guiding public energy planning policies and draws attention to the need to build strategic diesel stocks. economy end inputoutput input output direct indirect creation 10 (1 days structure sector specifically R7628 R 76 28 R$76.2 billion 15 1 5 1.5 201 18 8 1. jobs stocks ( R762 7 2 R$76. 20 R76 R$76 R7 R$7 R$

ABSTRACT Facility location-related decision problems pose a significant challenge for managers due to the multiple and conflicting factors involved. Moreover, incorrect decisions can lead to substantial impacts on companies' long-term strategic planning, resulting in losses for the business. This paper deals with a facility location problem in the educational sector in the northeast region of Brazil, which concerns the definition of the best location to place a private sector technical school, considering multiple objectives throughout a multicriteria approach. The decision-making process is structured based on a 9-step multicriteria model, and the preference elicitation phase is aided by the Flexible and Interactive Tradeoff (FITradeoff) method, using partial information provided by the decision-maker (DM). In the application presented in this paper, preference modeling is conducted considering the combination of two preference elicitation paradigms in the FITradeoff decision process: elicitation by decomposition and holistic evaluations, throughout a flexible approach. The DM’s preferences are elicited interactively, by means of a Decision Support System (DSS). At each interaction, the information given by the DM acts as constraints for a linear programming problem (LPP) model, which is computed in order to verify the potential optimality of each alternative. At the end of the elicitation process, a sensitivity analysis is performed so as to verify the robustness of the results obtained. Insights on the preference modeling paradigms combination with potential advantages for the decision process are also discussed in this paper. locationrelated related involved Moreover companies longterm long term planning business Brazil school approach decisionmaking making 9step step 9 model (FITradeoff method decisionmaker maker DM. . (DM) evaluations DMs s interactively DSS. DSS (DSS) interaction LPP (LPP alternative obtained (DM (DSS

ABSTRACT In various Multi-objective Programming (MOP) problems, decision-makers are often faced with a large set of efficient solutions, presenting a challenge in discerning and selecting the best solutions within this broad set. To overcome this, decision-makers can tune and optimize their preference function over this efficient set to identify the optimal solutions that align with their preferences. Most existing methods address such problems in the deterministic case, while we aim to tackle a new challenge by dealing with these problems in a stochastic environment, which increases their complexity. Indeed, we focus in this study on proposing an exact method to optimize two preference functions over the efficient set of a Multi-objective Stochastic Integer Linear Programming (MOSILP) problem in order to find the best compromise solutions without enumerating all elements of this efficient set. The proposed method is based on the combination of two techniques: the first one is called the L-shaped method, while the second one is an adaptation of the branch-and-bound strategy by reinforcing it with efficient cuts and tests, which allows the method to remove a large number of inefficient solutions within the search tree. Moreover, the method exhibits adaptability in addressing the general case involving multiple preference functions. A didactic example is presented for illustration, followed by a computational study evaluating the method’s efficacy and performance by solving randomly generated instances. Multiobjective Multi objective MOP (MOP decisionmakers decision makers preferences environment complexity Indeed MOSILP (MOSILP techniques Lshaped L shaped branchandbound branch bound tests tree Moreover illustration s instances

Abstract Variable renewable energies are leading the energy transition and power system flexibility has become a global priority. Incorporating short-term assessment into long-term planning is essential to capture the operational characteristics of generation and address flexibility issues. This paper presents a novel model for generation and transmission expansion planning with economic dispatch. In the generation expansion planning, the capacity expansion is optimized. In the economic dispatch problem, power plant operation, hydropower generation, and line transmission power flow are optimized. The model is a mixed-integer linear programming problem solved in MATLAB using Gurobi toolbox. A model is proposed to optimize the reservoir of hydropower systems and run-of-river. A case study for supplying Brazilian demand in 2050 is presented. A scenario with greenhouse gas emission costs and no deficit is proposed. This study has shown that the current penalty cost for loss of load is not sufficient to avoid a deficit. It is possible to supply 2050 demand, without large reservoirs or deficits, with a 5.5% curtailment, using 13% of total storage capacity, however; peaking power plants are required. priority shortterm short term longterm long issues optimized operation mixedinteger mixed integer toolbox runofriver. runofriver run river. river run-of-river 205 presented deficits 55 5 5.5 curtailment 13 however required 20 5. 1 2