A continuous approach to the design of physical distribution systems

Novaes, Antônio Galvão; Cursi, Eduardo Souza de; Graciolli, Odacir D.

doi:10.1016/s0305-0548(99)00063-5

Cited by 39 publications

(32 citation statements)

References 16 publications

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“…The authors' methodology is based on a sweep approach and assumes a rectangular grid structure. Novaes et al [18] present a methodology for solving the same problem as [19], but they used a continuous approach to represent the region. Previous works are extended by [20] introducing some improvements to the ring-radial model.…”

Section: Literature Reviewmentioning

confidence: 99%

A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances

González-Ramírez

Smith

Askin

et al. 2017

Mathematical Problems in Engineering

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We address a logistics districting problem faced by a parcel company whose operations consist of picking up and delivering packages over a service region. The districting process aims to find a partition of the service region into delivery and collection zones that may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed considering different instance sizes and types. Results show that the proposed solution approach is able to solve large-scale instances in reasonable computational times with good quality of the solutions obtained. To determine the quality of the solutions, results are compared with CPLEX solutions and with the current real solution to highlight the benefits of the proposed approach. Conclusions and recommendations for further research are provided.

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Section: Literature Reviewmentioning

confidence: 99%

A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances

González-Ramírez

Smith

Askin

et al. 2017

Mathematical Problems in Engineering

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“…Essa representação é justificada pelo fato de que os distritos tendem a ser alongados na direção do depósito (Newell e Daganzo, 1986). Extensões do modelo a situações com formas não geomé-tricas dos distritos, densidade variável, etc., podem ser desenvolvidas seguindo a metodologia apresentada por Novaes et al (2000) e Novaes et al (2009b). Quando os pontos de atendimento dentro do distrito se distribuem de maneira aproximadamente uniforme e independente (distribuição espacial de Poisson), e as zonas são razoavelmente compactas e convexas (Larson e Odoni, 1981), as distâncias reais entre pontos podem ser estimadas com razoável precisão através da multiplicação da distância teórica, calculada através da norma 2  (distância Euclidiana), por uma constante corretiva previamente ajustada (Novaes et al, 2000).…”

Section: Roteirização Estática Preliminarunclassified

“…em que, r 0 : distância Euclidiana do depósito à entrada das zonas 1 A , 2 A , e 3 A (vide Figura 1); 1 k  : coeficiente corretivo da distância Euclidiana para ajustá-la aproximadamente à rede viária (Newell e Daganzo, 1986;Novaes et al, 2000); e v: velocidade média nos percursos de ida e volta ao distrito.…”

Section: Suponhamos Então Queunclassified

Roteirização dinâmica de veículos usando simulação e algoritmo genético

et al. 2011

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Resumo: Problemas dinâmicos de roteirização de veículos têm recebido crescente atenção dos pesquisadores em função da rápida evolução das tecnologias de telecomunicação, do tratamento da informação e dos avanços observados nas técnicas de análise, otimização e computação. Nos centros urbanos sujeitos a congestionamentos de tráfego elevados e imprevisíveis, os operadores logísticos costumam alocar, muitas vezes, um número excessivo de tarefas aos seus veículos, acarretando o não cumprimento de atividades programadas ao fim da jornada diária, situação essa que leva à não realização dos compromissos logísticos assumidos com seus clientes. Neste artigo é analisado um problema de roteirização dinâmica, em que parte das tarefas em excesso, que venham a ocorrer nos roteiros programados, é transferida para um veículo auxiliar, que efetua, assim, um roteiro dinâmico constituído pelas atividades provenientes dos veículos regulares. Para resolver o problema, foi utilizado um algoritmo genético, associado à simulação para obtenção de parâme-tros relevantes.Palavras-chave: roteirização dinâmica, algoritmo genético, simulação.Abstract: Dynamic vehicle routing problems have received increasing attention in the literature due to the rapid evolution of telecommunication and information technologies, as well as advances in analytical and computational techniques. In large urban centers subject to critical and often unpredictable traffic congestion, logistics operators often use to allocate an excessive number of tasks to their vehicles, generating undone programmed activities at the end of the working day, thus impairing contractual obligations previously assumed with their clients. In this article, a dynamic routing problem is analyzed in which the tasks in excess, that might exceed the daily working time limit in a route, are assigned to an auxiliary vehicle, thus forming another dynamic route composed by the transferred tasks generated by the regular trucks. To solve the problem, a genetic algorithm was employed in association with a simulation program intended to get some relevant parameters.

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“…near optimal algorithms). Among the heuristic techniques are those based on evolutionary techniques (Novaes et al, 2000), construction and improvement algorithms (Gonzalez-Ramirez et al, 2010-2011Koskosidis and Powell, 1992), and those based on mathematical programming (Miranda and Garrido, 2004a). Based on the different problems and formulations observed, several criteria have been considered as performance indicator for the customer clustering, depending on the stage and level within Supply Chain Planning process addressed (i.e., strategic, tactical, or operational level).…”

Section: Introductionmentioning

confidence: 99%