Doutorado em Ciência da Computação
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Navegando Doutorado em Ciência da Computação por Autor "Amaral, André Renato Sales"
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- ItemALGORITMOS HEURÍSTICOS INTELIGENTES PARA PROBLEMAS DE LAYOUT EM LINHA ÚNICA E LINHA DUPLA(Universidade Federal do Espírito Santo, 2021-08-03) Cravo, Gildásio Lecchi; Amaral, André Renato Sales; https://orcid.org/0000-0001-7344-3994; http://lattes.cnpq.br/4695002674556067; https://orcid.org/0000-0003-2497-2835; http://lattes.cnpq.br/4301368869549226; Mauri, Geraldo Regis; https://orcid.org/0000-0002-8393-7741; http://lattes.cnpq.br/7870111209439581; Mestria, Mário; https://orcid.org/0000-0001-8283-0806; http://lattes.cnpq.br/5866381928751063; Boeres, Maria Claudia Silva; https://orcid.org/0000-0001-9801-2410; http://lattes.cnpq.br/0528154281423964; Lorenzoni, Luciano Lessa; https://orcid.org/0000-0003-4859-7750; http://lattes.cnpq.br/7959495705859101The study of layout of facilities aims to determine the best use of available space, resulting in more effective manufacturing processes in the context of industry. This thesis addresses four facility layout problems, categorized as row layout, in which facilities must be arranged in one or two straight lines, respecting some allocation constraints. Initially, the problem of single-row facility layout (SRFLP) is addressed, which consists of arranging facilities along a straight line, in order to minimize the weighted sum of the distances between all pairs of facilities. The other three problems addressed in this study are SRFLP extensions, in which the facilities are arranged in two lines, namely: the double-row layout problem (DRLP), the parallel row ordering problem (PROP) and the bi-objective corridor allocation problem (bCAP). An algorithm called GRASP-F is proposed for SRFLP. The computational experiments show the efficiency of the method by improving the known-values for 29 out of 93 instances in the literature with up to 1000 facilities. To date, this is the second work to consider problems of this magnitude. For DRLP, a purely heuristic approach, called PSO-DRLP, is proposed based on the Particle Swarm Optimization meta-heuristic. The PSO-DRLP presented values equal to or better than the known-values for 35 of 51 instances in the literature, and, for the remaining 16, the values found are very close to the best-known values. The solution algorithm for PROP, called AILS, is based on the ILS meta-heuristic, but unlike the standard, two phases with different intensification and diversification characteristics were used, in addition to using techniques to accelerate the calculation of the gain in the objective function in the neighborhood move used in the local search. The results found improved 49 out of 100 instances with previous known results and for the remaining 51 instances the best-known results were achieved. In addition to these tests, experiments were carried out using 6 instances with up to 300 facilities, unprecedented in the context of PROP. For bCAP, an algorithm similar to AILS-PROP was proposed, also in two phases and with techniques to accelerate the calculation of the gain in the objective function in the neighborhood movements used in the local search, having obtained excellent results for 76 tested instances. In general, the proposed solutions for the four problems can be considered excellent alternatives to solve layout problems in single and double lines, being possible to obtain high quality results for large problems in low computational times.
- ItemMatheurística com Abordagem Hierárquica Aplicada ao Problema de Roteamento de Veículos Capacitados e ao Problema de Roteamento de Helicópteros(Universidade Federal do Espírito Santo, 2021-10-27) Machado, André Manhães; Mauri, Geraldo Regis; https://orcid.org/0000-0002-8393-7741; http://lattes.cnpq.br/7870111209439581; https://orcid.org/0000-0002-8560-4473; http://lattes.cnpq.br/0364675276490227; Santos, Isaac Pinheiro dos; https://orcid.org/0000-0001-8524-0393; http://lattes.cnpq.br/3793156690673506; Ribeiro, Glaydston Mattos; https://orcid.org/0000-0001-8452-057X; http://lattes.cnpq.br/5401369683892150; Boeres, Maria Claudia Silva; https://orcid.org/0000-0001-9801-2410; http://lattes.cnpq.br/0528154281423964; Amaral, André Renato Sales; https://orcid.org/0000-0001-7344-3994; http://lattes.cnpq.br/4695002674556067; Lorenzoni, Luciano Lessa; https://orcid.org/0000-0003-4859-7750; http://lattes.cnpq.br/7959495705859101This work develops a hybrid matheuristic based on the approach Route-First-Cluster-Second (RFCS) by applying Greedy Randomized Adaptive Search Procedure (GRASP), mathematical models and Variable Neighborhood Search (VNS) to tackle two types of vehicle routing problems: the Capacitated Vehicle Routing Problem (CVRP) and the Helicopter Routing Problem (HRP). At rst, in the proposed method, a routing is performed using constructive heuristics and the Set Covering Problem (SCP). SCP employs local optima solutions found in previous iterations of VNS to create a partial tour which is lled by a constructive heuristic if needed. Then, the built solution undergoes a local search phase by VNS. This process is repeated as the main loop of the GRASP. As last step of the method, the Set Partitioning Problem (SPP) provides a new improved solution with regard to solutions found in the GRASP. In relation to the study problems, the CVRP consists of designing a set of routes for a eet of identical vehicles to attend a set of customers at shortest distance travelled, while the HRP aims of serving a set of transportation requests, dened as a pair of boarding and landing locations, using helicopters as the mode of transportation to minimize the cost of meeting the set of transportation requests. Besides, we propose a new HRP model to address unique characteristics of oshore platforms through a novel constraint to solve an issue that remains unnoticed until now: oshore platforms can be visited by helicopters one at a time. We also add the possibility to make multiple trips inside each route and enforce time window to attend passengers. Besides, the model has restrictions regarding to the total time of the ight, the fuel consumption, the total weight during the ight, the number of seats used by passengers. The matheuristic is proposed in two versions. The rst one solves the CVRP, and it is tested in seven benchmarks using other heuristics in the literature as a comparison. The second version is applied in two models of the HRP, where the method is tested in 37 instances with up to 1000 requests. Computational experiments showed that the proposed matheuristic for CVRP is competitive in terms of the quality for solutions reported in recent works. Moreover, in relation to the HRP, the matheuristic achieves results equal to or greater than other heuristics in 36 instances.
- ItemMeta-heurísticas para resolução de alguns problemas de planejamento e controle da produção(Universidade Federal do Espírito Santo, 2018-08-03) Bissoli, Dayan de Castro; Amaral, André Renato Sales; Moraes, Renato Elias Nunes de; Mauri, Geraldo Regis; Lorenzoni, Luciano Lessa; Sousa, Jorge Pinho deThis study addresses the resolution of three different problems, widely encountered in the real context of production planning and control. Initially, a GRASP metaheuristic is proposed to solve an assembly-line balancing problem (SALBP-2). The proposed method presented competitive results in relation to the literature, also focusing on a simplicity of operation to be applied in real cases. Subsequently, the same method was used to solve the Job Shop Scheduling Problem (JSP). The GRASP developed for the JSP also presented good results, with low average relative deviation in relation to the best solutions known in the literature. Next, we approached an extension of the JSP, the Flexible Job Shop Scheduling Problem (FJSP). The JSP is limited to the sequencing of operations on fixed machines, whereas in the FJSP the assignment of an operation is not preset and can thus be processed on a set of alternative machines. Therefore, the FJSP is not restricted to sequencing, extending in the assignment of operations to the appropriate machines (routing). The FJSP is more complex than the JSP because it considers the determination of the assignment of the machine for each operation. In order to solve the FJSP, we proposed four meta-heuristics: GRASP, Simulated Annealing (SA), Iterated Local Search (ILS) and Clustering Search (CS). SA presented lower results, however, incorporating it into a hybrid version of ILS, which uses it as a local search, the results improved, especially in more complex instances. Considering the hybrid characteristic of CS, the SA was also used, in this case as a solution-generating metaheuristic. This approach also presented superior results to SA. Both ILS and CS generated results with values equal to or close to those of the best known solutions for an extensive set of instances for the FJSP, as well as providing some new best known values.