PPGCC - Programa de Pós-graduação em Ciência da Computação
URI permanente desta comunidadehttp://www.hml.repositorio.ufop.br/handle/123456789/596
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Resultados da Pesquisa
Item Exact and heuristic approaches for traveling salesman problems with drones.(2021) Freitas, Júlia Cária de; Penna, Puca Huachi Vaz; Toffolo, Túlio Ângelo Machado; Penna, Puca Huachi Vaz; Toffolo, Túlio Ângelo Machado; Souza, Marcone Jamilson Freitas; Subramanian, AnandThe technological advances concerning drones have encouraged the market to consider drone applications in different areas including last mile delivery. However, limitations due to battery capacity, maximum weight, and legal regulations restrict the effective operational range of drones in many practical applications. To overcome the battery issue, hybrid operations involving one or more drones launching from a larger vehicle have emerged, in which the larger vehicle operates as a mobile depot and a recharging platform. In this dissertation, we describe a routing model that leverage the drone and truck working as a synchronized unit. The Flying Sidekick Traveling Salesman Problem (FSTSP) considers a delivery system composed by a truck and a drone. The drone launches from the truck with a single package to deliver to a customer. Each drone must return to the truck to recharge batteries, pick up another package, and launch again to a new customer location. This work proposes two novel Mixed Integer Programming (MIP) formulations and a heuristic approach to address the problem. The proposed MIP formulations yields better linear relaxation bounds than previously proposed formulations for all instances, and was capable of optimally solving several unsolved instances from the literature. We developed a hybrid heuristic based on the General Variable Neighborhood Search metaheuristic to tackle a generalization of the FSTSP called Multiple Traveling Salesman Problem with Drones, in which multiple trucks and drones are considered as part of the delivery system. The heuristic obtained high-quality solutions for large-size instances. The efficiency of the algorithm was evaluated on 410 benchmark instances from the literature, and over 80% of the best known solutions were improved.Item Mathematical models and heuristic algorithms for routing problems with multiple interacting components.(2021) Chagas, Jonatas Batista Costa das; Souza, Marcone Jamilson Freitas; Santos, André Gustavo dos; Souza, Marcone Jamilson Freitas; Santos, André Gustavo dos; Barboza, Eduardo Uchoa; Arroyo, José Elias Claudio; Vidal, Thibaut Victor Gaston; Toffolo, Túlio Ângelo MachadoMuitos problemas de otimização com aplicações reais têm vários componentes de interação. Cada um deles pode ser um problema pertencente à classe N P-difícil, e eles podem estar em conflito um com o outro, ou seja, a solução ótima para um componente não representa necessariamente uma solução ótima para os outros componentes. Isso pode ser um desafio devido à influência que cada componente tem na qualidade geral da solução. Neste trabalho, foram abordados quatro problemas de roteamento complexos com vários componentes de interação: o Double Vehicle Routing Problem with Multiple Stacks (DVRPMS), o Double Traveling Salesman Problem with Partial Last-InFirst-Out Loading Constraints (DTSPPL), o Traveling Thief Problem (TTP) e Thief Orienteering Problem (ThOP). Enquanto os DVRPMS e TTP já são bem conhecidos na literatura, os DTSPPL e ThOP foram recentemente propostos a fim de introduzir e estudar variantes mais realistas dos DVRPMS e TTP, respectivamente. O DTSPPL foi proposto a partir deste trabalho, enquanto o ThOP foi proposto de forma independente. Neste trabalho são propostos modelos matemáticos e/ou algoritmos heurísticos para a solução desses problemas. Dentre os resultados alcançados, é possível destacar que o modelo matemático proposto para o DVRPMS foi capaz de encontrar inconsistências nos resultados dos algoritmos exatos previamente propostos na literatura. Além disso, conquistamos o primeiro e o segundo lugares em duas recentes competições de otimização combinatória que tinha como objetivo a solução de uma versão bi-objetiva do TTP. Em geral, os resultados alcançados por nossos métodos de soluções mostraram-se melhores do que os apresentados anteriormente na literatura considerando cada problema investigado neste trabalho.Item Conflict graphs in mixed-integer linear programming : preprocessing, heuristics and cutting planes.(2020) Brito, Samuel Souza; Santos, Haroldo Gambini; Santos, Haroldo Gambini; Fonseca, George Henrique Godim da; Mateus, Geraldo Robson; Aragão, Marcus Vinicius Soledade Poggi de; Toffolo, Túlio Ângelo MachadoThis thesis addresses the development of con ict graph-based algorithms for MixedInteger Linear Programming, including: (i) an e cient infrastructure for the construction and manipulation of con ict graphs; (ii) a preprocessing routine based on a clique strengthening scheme that can both reduce the number of constraints and produce stronger formulations; (iii) a clique cut separator capable of obtaining dual bounds at the root node LP relaxation that are 19.65% stronger than those provided by the equivalent cut generator of a state-of-the-art commercial solver, 3.62 times better than those attained by the clique cut separator of the GLPK solver and 4.22 times stronger than the dual bounds obtained by the clique separation routine of the COIN-OR Cut Generation Library; (iv) an odd-cycle cut separator with a new lifting module to produce valid odd-wheel inequalities; (v) two diving heuristics capable of generating integer feasible solutions in restricted execution times. Additionally, we generated a new version of the COIN-OR Branch-and-Cut (CBC) solver by including our con ict graph infrastructure, preprocessing routine and cut separators. The average gap closed by this new version of CBC was up to four times better than its previous version. Moreover, the number of mixed-integer programs solved by CBC in a time limit of three hours was increased by 23.53%.