CoolSys: herramienta computacional de auxilio a la poscosecha de productos hortofrutícolas

CoolSys es un programa para el cálculo y simulado de procesos de enfriamiento y almacenamiento de productos hortofrutícolas, estructurado en cuatro módulos: Módulo de Almacenamiento e Compatibilidad; Módulo de Embalajes; Módulo de Propiedades Termofísicas y Módulo de Enfriamiento. El programa fue desarrollado en ambiente MS Visual Basic v. 5.0 y registrado por el Instituto Nacional da Propriedade Industrial (Brasil), para aplicación en el área de Tecnología de Poscosecha. Ventanas de fácil acceso conteniendo informaciones de los productos y procesos, así como figuras ilustrativas, creación de tablas, gráficos y archivos de datos, permiten al usuario una buena comprensión así como la impresión de relatórios

Algrorithms for the routing meter readers problem

Orientador: Paulo Morelato FrançaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: Esse trabalho se dedicou ao estudo dos algoritmos para roteamento de leituristas, incluindo propostas de alteração que resultem na melhoria da qualidade dos resultados. A motivação é proveniente da alta demanda por soluções computacionais para esse problema, ainda pouco estudado devido às peculiaridades que lhe são inerentes. Encontram-se na literatura duas heurísticas, de estratégias distintas e antagônicas para esse problema. Uma das heurísticas procura construir a rota ignorando a restrição de capacidade, para posterior particionamento dessa rota em subrotas, cada qual destinada a um leiturista (¿route first, cluster second¿). A outra heurística, em uma abordagem inversa, primeiramente subdivide a região de trabalho dos leituristas, para posterior roteamento dessas partições (¿cluster first, route second¿). Essas duas heurísticas foram testadas exaustivamente, tornando possível localizar aspectos sujeitos à melhoria, dando origem a duas novas heurísticas. Foi gerada uma base de testes contendo 144 instâncias que simulam as condições reais de trabalho dos leituristas, classificadas de acordo com o tamanho e dificuldade. A partir das soluções provenientes dos quatro algoritmos foi possível analisá-los comparativamente, avaliando o melhor em um âmbito geral (envolvendo todos os algoritmos) e específico (algoritmos de mesmo tipo, ¿route first cluster second¿ ou ¿cluster first route second¿), segundo critérios de qualidade pré-definidos: número de rotas, tempo de percurso, violação da carga horária e tempo computacional. Os resultados revelam que os novos algoritmos foram melhores tanto na comparação específica quanto na comparação geralAbstract: This work¿s main study object consists on algorithms for routing meter readers, from which proposals towards solution¿s improvement are made. The demand for computational results concerning this problem, added to literature little attention due to its inherited peculiarities, has been the outmost motivation. Two preexisting heuristics from literature, with distinct and antagonic strategies, are pointed out. One of these heuristics atempt to create a single route, dismissing the capacity restriction, and then partitionates this route into subroutes, each of them destinated to one meter reader (route first, cluster second). The other heuristic, in an inverse approach, first splits the meter reader¿s working area, and only then routes each of these partitions (cluster first, route second). The two heuristics were tested to exaustion, allowing enumeration of weak aspects subject to improvement. Therefore, two new heuristics were developed, based upon the originals, however adapted in order to outperform solution¿s quality. A testing base containing 144 instances was generated, simulating meter readers realistic labor¿s conditions, classified by size and difficulty. Through solutions provided by the four algorithms, comparison analyses have taken place, evaluating in a general (involving all algorithms) and specific manner (same kind algorithms, i.e., route first, cluster second or cluster first, route second), considering four predefined quality criteria: number of routes, deadheading time, violation of shiftwork time and computational time. Results revealed that the new algorithms achieved better solutions on specific and general comparisonsMestradoAutomaçãoMestre em Engenharia Elétric

Heuristic and exact approaches for the open capacitated arc routing problem

Orientadores: André Luiz Morelato França, Paulo Morelato FrançaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo:O problema de roteamento em arcos capacitado e aberto (open capacitated arc routing problem, OCARP) é um problema de otimização combinatorial NP-difícil em que, dado um grafo não-direcionado, o objetivo consiste em encontrar um conjunto de rotas de custo mínimo para veículos com capacidade restrita que atendam a demanda de um subconjunto de arestas. O OCARP está relacionado com o problema de roteamento em arcos capacitado (capacitated arc routing problem, CARP), mas difere deste pois o OCARP não possui um nó depósito e as rotas não estão restritas a ciclos. Aplicações da literatura para o OCARP são discutidas. Uma formula ção de programação linear inteira é fornecida junto com propriedades do problema. Uma metaheurística GRASP (greedy randomized adaptive search procedure) com reconexão por caminhos (path-relinking) é proposta e comparada com outras metaheurísticas bem-sucedidas da literatura. Algumas características do GRASP são: (i) ajuste reativo de parâmetros, cujos valores são estocasticamente selecionados com viés 'aqueles valores que produziram, em média, as melhores soluções; (ii) um filtro estatístico que descarta soluções iniciais caso estas tenham baixa probabilidade de superar a melhor solução incumbente; (iii) uma busca local infactível que gera soluções de baixo custo utilizadas para explorar fronteiras factíveis/infactíveis do espaço de soluções; (iv) a reconexão por caminhos evolutiva aprimora progressivamente um conjunto de soluções de elevada qualidade (soluções elites). Testes computacionais foram conduzidos com instâncias CARP e OCARP e os resultados mostram que o GRASP é bastante competitivo, atingindo os melhores desvios entre os custos das soluções e limitantes inferiores conhecidos. Este trabalho também propõe um algoritmo exato para o OCARP que se baseia no paradigma branch-and-bound. Três limitantes inferiores são propostos e um deles utiliza o método dos subgradientes para resolver uma relaxação lagrangeana. Testes computacionais comparam o algoritmo branch-and-bound com o CPLEX resolvendo um modelo reduzido OCARP de programa ção linear inteira. Os resultados revelam que o algoritmo branch-and-bound apresentou resultados melhores que o CPLEX no que diz respeito aos desvios entre limitantes e ao número de melhores soluçõesAbstract: The Open Capacitated Arc Routing Problem (OCARP) is an NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours that services a subset of edges with positive demand under capacity constraints. This problem is related to the Capacitated Arc Routing Problem (CARP) but differs from it since OCARP does not consider a depot, and tours are not constrained to form cycles. Applications to OCARP from literature are discussed. An integer linear programming formulation is given, followed by some properties of the problem. A Greedy Randomized Adaptive Search Procedure (GRASP) with path-relinking (PR) solution method is proposed and compared with other successful metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the metaheuristic parameters values are stochastically selected biased in favor of those values which produced the best solutions in average; (ii) a statistical filter, which discards initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend in which a pool of elite solutions is progressively improved by relinking pairs of elite solutions. Computational tests were conducted for both CARP and OCARP instances, and results reveal that the GRASP with PR is very competitive, achieving the best overall deviation from lower bounds. This work also proposes an exact algorithm for OCARP, based on the branch-and-bound paradigm. Three lower bounds are proposed, one of them uses a subgradient method to solve a Lagrangian relaxation. The computational tests compared the proposed branch-and-bound with a commercial state-of-the-art ILP solver. Results reveal that the branch-and-bound outperformed CPLEX in the overall average deviation from lower boundsDoutoradoAutomaçãoDoutor em Engenharia Elétric

A parameterized lower bounding method for the open capacitated arc routing problem

Consider an undirected graph with demands scattered over the edges and a homogeneous fleet of vehicles to service the demands. In the open capacitated arc routing problem (OCARP) the objective is to find a set of routes that collectively service all demands with the minimum cost. Each vehicle has limited capacity and it can start and finish the route at any node. The OCARP is NP-hard, and its applications include meter reading and cutting path determination problems. State-of-the-art solution methods developed for the OCARP are heuristics, which show good tradeoffs between solution quality and processing time, but do not provide optimality certificates of the obtained solutions. This work focuses on a lower bounding method for the OCARP which can be used to better assess the quality of heuristic solutions. We propose the Relaxed Flow method (RF(k)) which involves the resolution of a mixed integer linear formulation where all vehicles' capacities are modeled as flows on an augmented graph. A parameter k controls the model tightness and RF(k) is shown to be at least as tight as the well-known Belenguer and Benavent's formulation for any k⩾0. To strengthen the model, capacity cuts were included in RF(k) by means of a branch-and-cut framework. Extensive computational experiments conducted on a set of benchmark instances revealed that our method outperformed previous methods. Computational experiments also demonstrated the importance of the parameterization technique to obtain good results. The previously known lower bounds were improved substantially and optimality certificates were attained in 78.9% of the instances. As far as we know this is the first parameterized lower bounding method proposed for an arc routing problem, and we argue it can be generalized to other variants of arc routing problems and general routing problems

Branch-and-cut algorithms for the covering salesman problem

The Covering Salesman Problem (CSP) is a generalization of the Traveling Salesman Problem in which the tour is not required to visit all vertices, as long as all vertices are covered by the tour. The objective of CSP is to find a minimum length Hamiltonian cycle over a subset of vertices that covers an undirected graph. In this paper, valid inequalities from the generalized traveling salesman problem are applied to the CSP in addition to new valid inequalities that explore distinct aspects of the problem. A branch-and-cut framework assembles exact and heuristic separation routines for integer and fractional CSP solutions. Computational experiments show that the proposed framework outperformed methodologies from literature with respect to optimality gaps. Moreover, optimal solutions were proven for several previously unsolved instances

GRASP with evolutionary path-relinking for the capacitated arc routing problem

The Capacitated Arc Routing Problem (CARP) is a well-known NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours servicing a subset of required edges under vehicle capacity constraints. There are numerous applications for the CARP, such as street sweeping, garbage collection, mail delivery, school bus routing, and meter reading. A Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) is proposed and compared with other successful CARP metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the parameter value is stochastically selected biased in favor of those values which historically produced the best solutions in average; (ii) a statistical filter, which discard initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend where the pool of elite solutions is progressively improved by successive relinking of pairs of elite solutions. Computational tests were conducted using a set of 81 instances, and results reveal that the GRASP is very competitive, achieving the best overall deviation from lower bounds and the highest number of best solutions found. © 2011 Elsevier Ltd. All rights reserved

M.: The open capacitated arc routing problem

Abstract The Open Capacitated Arc Routing Problem (OCARP) is a new NP-hard combinatorial optimization problem where we must find a set of minimum cost paths which covers all required edges from an undirected graph under capacity constraints. This problem is based upon the Capacitated Arc Routing Problem (CARP) but differs from it since OCARP does not comply a depot and routes are not constrained to form cycles. An integer linear programming formulation followed by some usefull properties are given. The similarity between OCARP and other problems reported in literature has been exploited to derive practical (polynomial) reductions. Computational tests were conducted with an adapted path-scanning heuristic from literature applied to a set of 81 instances. Results show the first lower and upper bounds, where proven optimality was obtained to 19 instances

Hierarchical multiple criteria optimization of maintenance activities on power distribution networks

Power distribution utilities must transport quality and reliable electric energy to all of the customers in a given network within specified targets. Failure of one of the network components is the main factor that compromises a system’s reliability. Maintenance actions, such as repairs and component replacements, are employed to avoid power interruptions or to resume the healthy network operation. This paper reports the relationship between maintenance activities and reliability as an optimization problem with two criteria: cost of maintenance activities and the maximum value for a system average interruption frequency index planning period. Solving these problems for each network provides local efficient solutions and associated trade-off curves. These solutions are optimally combined to solve a global-level multiple criteria optimization problem, revealing the local efficient solutions and associated trade-off curves for a group of networks or for a whole company. The procedure solves the hierarchical multiple criteria maintenance resources allocation problem and provides information to assess the decisions on maintenance activities at all decision levels in the network management. This procedure is applied to one illustrative example and real-life case studies to demonstrate its benefits2241171192CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQnão te