Claudio Barbieri da Cunha

A genetic algorithm for the problem of configuring a hub-and-spoke network for a LTL trucking company in Brazil

Abstract A heuristic based on genetic algorithms is proposed to the problem of configuring hub-and-spoke networks for trucking companies that operate less-than-truckload (LTL) services in Brazil. The problem consists of determining the number of consolidation terminals (also known as hubs), their locations and the assignment of the spokes to the hubs, aiming to minimize the total cost, which is composed of fixed and variable costs. The proposed formulation differs from similar formulations found in the literature in the sense that it allows variable scale-reduction factors for the transportation costs according to the total amount of freight between hub terminals, as occurs to less-than-truckload (LTL) freight carriers in Brazil. Our genetic algorithm approach incorporates an efficient local improvement procedure that is applied to each generated individual of the population. Computational results for benchmark problems are presented. A practical application to a real world problem involving one of the top-ten trucking companies in Brazil is also described.

New simple and efficient heuristics for the uncapacitated single allocation hub location problem

Hub-and-spoke networks are widely studied in the area of location theory. They arise in several contexts, including passenger airlines, postal and parcel delivery, and computer and telecommunication networks. Hub location problems usually involve three simultaneous decisions to be made: the optimal number of hub nodes, their locations and the allocation of the non-hub nodes to the hubs. In the uncapacitated single allocation hub location problem (USAHLP) hub nodes have no capacity constraints and non-hub nodes must be assigned to only one hub. In this paper, we propose three variants of a simple and efficient multi-start tabu search heuristic as well as a two-stage integrated tabu search heuristic to solve this problem. With multi-start heuristics, several different initial solutions are constructed and then improved by tabu search, while in the two-stage integrated heuristic tabu search is applied to improve both the locational and allocational part of the problem. Computational experiments using typical benchmark problems (Civil Aeronautics Board (CAB) and Australian Post (AP) data sets) as well as new and modified instances show that our approaches consistently return the optimal or best-known results in very short CPU times, thus allowing the possibility of efficiently solving larger instances of the USAHLP than those found in the literature. We also report the integer optimal solutions for all 80 CAB data set instances and the 12 AP instances up to 100 nodes, as well as for the corresponding new generated AP instances with reduced fixed costs.

A spreadsheet-based optimization model for the integrated problem of producing and distributing a major weekly newsmagazine

Abstract In this paper, we address the problem of producing and distributing the Brazilian newsmagazine E poca , a major weekly publication with one of the 10 largest circulations in the world. This real-world problem had been puzzling magazine publishers in Brazil and remained unsolved for many years. We propose an innovative mixed-integer-linear programming model to determine the number and location of the industrial facilities that should produce the magazines, what destinations should be assigned to each selected facility; the production sequencing and the modes of transportation (air or truck). Our model aims to minimize the total cost while adhering to production capacity and time constraints. The model was implemented in an electronic spreadsheet environment and yielded a savings of 7.1% of the total costs. Given that despite their huge popularity, little has been written on the issues of implementing full-scale optimization models in spreadsheets; thus we also provide the details of the model’s implementation in Excel.

Very Large-Scale Neighborhood Search for the K-Constraint Multiple Knapsack Problem

The K-Constraint Multiple Knapsack Problem (K-MKP) is a generalization of the multiple knapsack problem, which is one of the representative combinatorial optimization problems known to be NP-hard. In K-MKP, each item has K types of weights and each knapsack has K types of capacity. In this paper, we propose several very large-scale neighborhood search (VLSN) algorithms to solve K-MKP. One of the VLSN algorithms incorporates a novel approach that consists of randomly perturbing the current solution in order to efficiently produce a set of simultaneous non-profitable moves. These moves would allow several items to be transferred from their current knapsacks and assigned to new knapsacks, which makes room for new items to be inserted through multi-exchange movements and allows for improved solutions. Computational results presented show that the method is effective, and provides better solutions compared to exact algorithms run for the same amount of time.

A tabu search heuristic for the uncapacitated single allocation p-hub maximal covering problem

Abstract This paper describes a tabu search (TS) heuristic for the uncapacitated single allocation p-hub maximal covering problem. The objective is to determine the best location for p hubs and the assignment of each of the spokes to a single hub such that the total demand between pairs of nodes within a given coverage distance is maximized. We consider all nodes as possible candidates for establishing hub facilities, what increases the complexity of the problem. Based on the mathematical programming formulation proposed by Peker and Kara (2015) we also report, for the first time, the optimal solutions for instances with up to 50 nodes from the AP (Australian Post) benchmark dataset, as well as the complete set of results for the CAB (Civil Aeronautics Board) dataset, including some heretofore yet unpublished results. The computational experiments have also demonstrated that our TS heuristic is efficient, leading to improved solutions in shorter CPU times when compared to previously published results, as well as for new derived instances with tigher coverage. It was also able to solve, for the first time, all instances of the AP data set, with up to 200 nodes, as well as new instances with tighter coverage parameters, thus evidencing it capacity to solve effectively large, realistic-sized instances of the problem.

An ABC heuristic for optimizing moveable ambulance station location and vehicle repositioning for the city of São Paulo

In this paper, we address the problem of determining the optimal location of ambulance stations, as well as the vehicle allocation and repositioning for the mobile emergency care service of Sao Paulo (SAMU-SP), in Brazil. This problem arises in the context of seeking to reduce expected ambulance response times, which was within 27 minutes in Sao Paulo for 98% of the requests. In order to bring down total response times closer to internationally acceptable standards, SAMU-SP devised the concept of moveable ambulance stations that can be installed in available public spaces, such as squares and parks, and can be periodically relocated to ensure a good coverage at all times. This new concept, however, was not an easy sell. It was necessary to demonstrate clearly the benefits that such stations, if properly located, could provide in the context of limited budgetary resources when compared to the traditional facilities in regular buildings. In this context, we propose a novel artificial bee colony (ABC) algorithm to guide SAMU-SP in its strategic decisions involving their service network, as well as in the allocation and repositioning of ambulances to each stand-by point in order to cope with varying demand at different time periods. This model was applied to analyze different scenarios, including one that was implemented in the short term and yielded an improvement of over 40% in the expected coverage.

A mathematical model for the problem of sequencing and scheduling visits by bank managers

Este artigo aborda um problema real de sequenciamento (roteirizacao) e programacao de visitas domiciliares realizadas diariamente por um conjunto de gerentes de uma instituicao bancaria. As visitas, com hora marcada, sao agendadas por telefone a partir de um sistema tipo tele-atendimento e devem ser programadas ate o final do dia, para atendimento no dia seguinte. Os gerentes estao alocados em diferentes agencias. Isso pode ser formulado como um problema de roteirizacao e programacao de veiculos com restricoes de janela de tempo e multiplas bases. Ao contrario da quase totalidade dos problemas reais que envolvem roteirizacao e programacao de veiculos, que requerem heuristicas em funcao de sua complexidade combinatoria, as caracteristicas particulares do problema em questao permitiram sua simplificacao e solucao por intermedio de um algoritmo exato, por sua representacao como um problema de fluxo em rede. O algoritmo proposto foi implementado e aplicado com sucesso ao problema.

A heuristic approach to stowing general cargo into platform supply vessels

This paper addresses a practical problem encountered in the oil industry, related to the supplying of general cargo to offshore rigs and production units. For a given route assigned to a supply vessel we seek to determine the optimal two-dimensional positioning of deck cargoes such that the overall profit is maximized, while ensuring that several safety and operational constraints are respected. In terms of mathematical modelling, the resulting problem can be seen as a rich variation of the two-dimensional knapsack problem, since some cargoes may wait for a later trip. Furthermore, given that the trip may serve many offshore units and that a substantial number of items must also return from these units, the problem becomes even more complex and can be viewed as a pickup and delivery allocation problem. We propose a probabilistic constructive procedure combined with a local search heuristic to solve this problem. We also report the results of computational experiments with randomly generated instances. These results evidence that our proposed heuristic can effectively help ship planners when dealing with such large-scale allocation problems, with many operational constraints.

Sistema de apoio à decisão baseado em planilha eletrônica para otimização da programação de entrega de concreto pronto

This paper addresses a spreadsheet-based decision support system (DSS) for the problem of scheduling the delivery of ready mix concrete produced in concrete batch plants or centers taking into consideration the Brazilian reality. Such scheduling comprises decisions of what facility should serve each customer and what time each delivery vehicle should be loaded, so as to maximize the total marginal revenue of the system. Vehicle loading capacity constraints per center, fleet availability and ensuring that each clients orders are fulfilled by a single plant are considered. In order to solve this optimization problem efficiently we propose a mathematical programming model based on a time-space network. The spreadsheet-based DSS, novel in the literature, allows a concrete company which operates several concrete batch plants company to schedule its daily operations in an easy and straightforward manner, by users with no background in operations research, thus making it especially suitable for companies that are not ready or whose size does not allow the investment in a corporate system to aid the scheduling.

SISTEMA DE APOIO À DECISÃO PARA A OTIMIZAÇÃO DA ROTEIRIZAÇÃO DA SEPARAÇÃO MANUAL DE PEÇAS EM ARMAZÉM UTILIZANDO PLANÍLHAS ELETRÔNICAS

O presente trabalho trata do problema da determinacao de rota de separacao manual de pecas em armazens que minimize a distância total percorrida pelo separador. O problema abordado e pratico e comum a varias empresas, com impacto nos custos operacionais e relevância para a assertividade em relacao aos itens coletados. Ainda assim, o tema e pouco explorado nos estudos de roteirizacao disponiveis em lingua portuguesa e muitas empresas optam por confiar nas rotas criadas empiricamente pelos separadores. O metodo de roteirizacao proposto e baseado em programacao dinâmica e foi implementado em ambiente de planilha eletronica. O algoritmo utilizado como metodo de solucao e eficiente, flexivel e generico para ser utilizado em armazens com dois corredores transversais, independente da politica de localizacao ou separacao adotada e, por sua facilidade de implementacao e utilizacao, representa uma alternativa de roteirizacao eficiente e de baixo custo para pequenas e medias empresas.