The multicommodity traveling salesman problem with priority prizes: a mathematical model and metaheuristics

Artigo científico.The classic Traveling Salesman Problem (TSP) only considers the costs involved in the routes and does not differentiate products or customers. Logistic companies face conflict between operational costs, customers with different categories of products, and customer satisfaction, which is directly related to delivery time. This paper presents a new mathematical model for a TSP with variable costs and priority prizes, taking into account the customer’s product and preference values. This problem is denoted as the Multicommodity Traveling Salesman Problem with Priority Prizes (MTSPPP). Two versions of the Biased Random-Key Genetic Algorithm (BRKGA) are proposed to solve medium and large instances of the MTSPPP. Computational tests were performed, using modified instances based on classical TSP instances. The proposed methods have proved to be efficient in solving the MTSPPP.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Exact Algorithms for Mixed-Integer Multilevel Programming Problems

We examine multistage optimization problems, in which one or more decision makers solve a sequence of interdependent optimization problems. In each stage the corresponding decision maker determines values for a set of variables, which in turn parameterizes the subsequent problem by modifying its constraints and objective function. The optimization literature has covered multistage optimization problems in the form of bilevel programs, interdiction problems, robust optimization, and two-stage stochastic programming. One of the main differences among these research areas lies in the relationship between the decision makers. We analyze the case in which the decision makers are self-interested agents seeking to optimize their own objective function (bilevel programming), the case in which the decision makers are opponents working against each other, playing a zero-sum game (interdiction), and the case in which the decision makers are cooperative agents working towards a common goal (two-stage stochastic programming). Traditional exact approaches for solving multistage optimization problems often rely on strong duality either for the purpose of achieving single-level reformulations of the original multistage problems, or for the development of cutting-plane approaches similar to Benders\u27 decomposition. As a result, existing solution approaches usually assume that the last-stage problems are linear or convex, and fail to solve problems for which the last-stage is nonconvex (e.g., because of the presence of discrete variables). We contribute exact finite algorithms for bilevel mixed-integer programs, three-stage defender-attacker-defender problems, and two-stage stochastic programs. Moreover, we do not assume linearity or convexity for the last-stage problem and allow the existence of discrete variables. We demonstrate how our proposed algorithms significantly outperform existing state-of-the-art algorithms. Additionally, we solve for the first time a class of interdiction and fortification problems in which the third-stage problem is NP-hard, opening a venue for new research and applications in the field of (network) interdiction

Novas formulações de fluxo para problemas de otimização combinatória

Neste trabalho aborda-se o Problema de Minimização de Trocas de Ferramentas (PMTF) e o Problema do Caixeiro Viajante Multiproduto com Prioridades (PCVMP). O PMTF consiste em determinar um sequenciamento de tarefas, de tal modo que a quantidade de trocas de ferramentas entre as tarefas seja a menor possível. Cada tarefa requer um conjunto de ferramentas distinto, e supõe-se que cada um destes conjuntos não contenha mais ferramentas do que suporta a máquina. Já o PCVMP consiste em determinar uma rota de entrega de mercadorias considerando ao mesmo tempo, o cliente e o vendedor, ou seja, minimizando os custos totais do vendedor e maximizando as preferências dos clientes. Neste estudo tem-se como objetivo modelar, baseado em fluxo multicommodity, os problemas citados. Modelos matemáticos de otimização foram propostos assim como alguns resultados teóricos foram desenvolvidos. No caso do PMTF, o melhor modelo proposto foi comparado com os modelos existentes na literatura, mostrando um melhor desempenho tanto em quantidade de instâncias resolvidas na otimalidade, quanto no valor da relaxação linear e no tempo de execução. Mostrou-se que o valor da relaxação linear nos modelos propostos corresponde a diferença entre a quantidade de ferramentas e a capacidade da máquina. Algumas matheurísticas baseadas em busca por proximidade e um método exato enumerativo considerando eliminação de simetria foram propostos e comparados com os resultados da literatura. Já no caso do PCVMP, o modelo proposto se mostrou eficiente em resolver instâncias de pequeno e médio porte. Duas metaheurísticas, BRKGA e BRKGA adaptativo, ambas com busca local, também foram propostas para o PCVMP, apresentando bons resultados.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES