Clustering search

This paper presents the Clustering Search (CS) as a new hybrid metaheuristic, which works in conjunction with other metaheuristics, managing the implementation of local search algorithms for optimization problems. Usually the local search is costly and should be used only in promising regions of the search space. The CS assists in the discovery of these regions by dividing the search space into clusters. The CS and its applications are reviewed and a case study for a problem of capacitated clustering is presented.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal do MaranhãoUniversidade Federal de São Paulo (UNIFESP)Instituto Nacional de Pesquisas EspaciaisUNIFESPSciEL

Proposta de Modelo Matemático para o Problema de Roteamento de Sondas de Intervenção a Poços de Petróleo Terrestres Revelados Dinamicamente com Período de Atendimento Viável

Durante a fase de produção em poços de petróleo terrestres uma das atividades mais importantes e caras é o uso de sondas de intervenção. O funcionamento de cada um desses poços ocorre, na maioria das vezes, em condições difíceis com perfil de produção com grande variação em função da sua geologia, localização e a maneira como o poço é desenvolvido. Estas características levam ao longo da vida produtiva dos poços à necessidade de intervenções de manutenção nomeadas como workover, que são fundamentais para manter a produção ou mesmo melhorar a produtividade ao corrigir falhar que tipicamente ocorrem nos equipamentos dos poços. Como as sondas de intervenção são equipamentos caros e, por isto, em menores quantidades comparadas a quantidade de poços terrestres que demandam intervenções de manutenção, ocorre a geração de filas de poços aguardando atendimento. Isto leva a necessidade de geração de rotas de atendimento aos diferentes poços com as escassas sondas existentes, desafio conhecido como Problema de Roteamento de Sondas de Intervenção (PRSI). Na literatura, verificam-se modelos e métodos de solução para o PRSI estático, ou seja, que busca minimizar a perda total de produção, não considerando a possibilidade de novas informações relevantes para o roteamento serem reveladas ao longo do horizonte de planejamento. Sendo assim, busca-se neste trabalho estudar e propor um modelo matemático com abordagem dinâmica para o PRSI que minimize a perda total de produção dos poços revelados ao longo de um horizonte de planejamento. O PRSI Dinâmico foi resolvido ao ser criado algoritmo estrutural executado ao longo de um horizonte de planejamento, contendo o modelo matemático proposto, linearizado para execução no solver CPLEX, utilizando técnicas de Programação Linear Inteira Mista. Os resultados computacionais foram obtidos considerando instâncias geradas artificialmente, e a conclusão dessa pesquisa mostra que o modelo proposto aproxima o PRSI Dinâmico do contexto operacional do problema, o que impacta no processo de definição das rotas e agendamento dos atendimentos

Construction-based metaheuristics for personnel scheduling problems

This thesis investigates the idea of balancing different constraints in order to find optimal solutions to two personnel scheduling problems, within the framework of constructive metaheuristic approaches. The two problems considered are a nurse scheduling problem, for which finding feasible solutions is known to be difficult and for which the hard and soft constraints are in direct conflict, and a medical student scheduling problem for which there is little relevant literature this second problem also has conflicting hard and soft constraints, but presents further conflict between the different soft constraints. The methods used to solve these problems are focused on two constructive metaheuristics in particular: Greedy Randomised Adaptive Search Procedures (GRASP) and Ant Colony Optimisation (ACO) and for each approach several construction heuristics are introduced and compared. Using GRASP, a number of local search neighbourhoods are established for each problem, while for ACO the suitability of three trail definitions are compared. In order to further explore the balance which may obtained between the different constraints and objectives for the two problems, hybrid constructions are investigated, incorporating exact methods which take advantage of the underlying structures of each problem with regards to feasibility. For medical student scheduling, this exact method was developed into a new type of construction mechanism providing much improved results over a standard heuristic approach. Further enhancements investigated include the use of problem-specific feedback for nurse scheduling and the use of an intelligent memory procedure for the medical student scheduling problem. For the nurse scheduling problem, the final algorithm developed was able to rival the best in the literature so far and produce optimal solutions for all available datasets. For the medical student scheduling problem, optimal solutions are not known, but the results obtained are very promising and provide a good basis for further study of the problem.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Um algoritmo de busca híbrido para o problema de roteamento de embarcações de suprimento periódico

High quality maritime petroleum transportation is critical to ensure timely flow of goods, reducing the total logistics cost and guaranteeing an efficient process. In this thesis, we focus on the transportation of deck cargo to offshore units as observed in the operations of our industrial partner in Rio de Janeiro, Brazil. The main objective of this research is to define the maritime routes to solve a periodic supply vessels routing problem, taking into account the port departure and opening hours at the offshore facilities. We describe the solution procedures currently used by the company, and we formally formulate the problem mathematically. Given that the sizes of the instances are too large to be solved exactly, we propose different methods to achieve better solutions with a reduced computational time. The first method, composed of three phases, uses a clustering heuristic combined with an exact method in order to perform the routing and ends with a resenquencing according to the operating hours, port departures and time between services constraits. The second method uses the adaptive large neighborhood search (ALNS) heuristic in an attempt to reduce the number of operations performed by the previous heuristic and the computational time. Finally, a hybrid method is proposed based on the ALNS heuristic and innovates with the concepts of the clustering search algorithm that proposes a detection of promising regions of the search space. The computational results indicate that the hybrid heuristic brings benefits to the ALNS by finding better solutions in less time and still reduces the coefficient of variation within a sample of solutions in different executions.O transporte marítimo de petróleo de alta qualidade é fundamental para assegurar um fluxo de mercadorias dentro do prazo previsto, reduzindo o custo total da logística e garantindo operações eficientes. Nesta tese, o focus está no transporte de carga de convés para unidades marítimas como observado nas operações do parceiro industrial no Rio de Janeiro, Brasil. O principal objetivo desta pesquisa é definir as rotas marítimas para resolver um problema de roteamento de embarcações de suprimento periódico, levando em consideração a programação do porto e o horário de abertura em algumas instalações. Os procedimentos atualmente utilizados pela empresa são descritos, e o problema é matematicamente formulado. Dado que o tamanho das instâncias é muito grande para serem resolvidos exatamente, propõem-se diferentes métodos visando alcançar melhores soluções com um baixo tempo computacional. O primeiro método, composto por três fases, usa uma heurística de agrupamento de unidades marítimas combinada a um método exato a fim de realizar o roteamento das mesmas e finaliza com o sequenciamento das rotas de acordo com as restrições de horários de funcionamento, partidas do porto e tempo entre atendimentos. O segundo método utiliza a heurística adaptive large neighborhood search (ALNS) na tentativa de reduzir a quantidade de operações realizadas pela heurística anterior e o tempo computacional. Por fim, propõe-se um método híbrido baseando-se na heurística ALNS e inovando com conceitos do algoritmo clustering search que propõe uma detecção de regiões promissoras do espaço de busca. Os resultados computacionais indicam que a heurística híbrida traz benefícios ao ALNS ao encontrar melhores soluções em menos tempo e ainda reduz o coeficiente de variação dentro de uma amostra de soluções em diferentes execuções

Construction-based metaheuristics for personnel scheduling problems.

This thesis investigates the idea of balancing different constraints in order to find optimal solutions to two personnel scheduling problems, within the framework of constructive metaheuristic approaches. The two problems considered are a nurse scheduling problem, for which finding feasible solutions is known to be difficult and for which the hard and soft constraints are in direct conflict, and a medical student scheduling problem for which there is little relevant literature this second problem also has conflicting hard and soft constraints, but presents further conflict between the different soft constraints. The methods used to solve these problems are focused on two constructive metaheuristics in particular: Greedy Randomised Adaptive Search Procedures (GRASP) and Ant Colony Optimisation (ACO) and for each approach several construction heuristics are introduced and compared. Using GRASP, a number of local search neighbourhoods are established for each problem, while for ACO the suitability of three trail definitions are compared. In order to further explore the balance which may obtained between the different constraints and objectives for the two problems, hybrid constructions are investigated, incorporating exact methods which take advantage of the underlying structures of each problem with regards to feasibility. For medical student scheduling, this exact method was developed into a new type of construction mechanism providing much improved results over a standard heuristic approach. Further enhancements investigated include the use of problem-specific feedback for nurse scheduling and the use of an intelligent memory procedure for the medical student scheduling problem. For the nurse scheduling problem, the final algorithm developed was able to rival the best in the literature so far and produce optimal solutions for all available datasets. For the medical student scheduling problem, optimal solutions are not known, but the results obtained are very promising and provide a good basis for further study of the problem