The multimode covering location problem

Colombo, Fabio; Cordone, Roberto; Lulli, Guglielmo

doi:10.1016/j.cor.2015.09.003

Cited by 23 publications

(7 citation statements)

References 24 publications

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“…De acordo com Colombo et al (2016), um problema de localização de instalações consiste basicamente em definir a localização geográfica de uma série de instalações de forma a atender a um conjunto de centros de demanda cujas posições são conhecidas, e buscando otimizar uma determinada função objetivo.…”

Section: Problema De Localizaçãounclassified

Localização De Instalações Indesejáveis No Contexto Da Gestão De Desastres

Calazans¹,

Samed²

2018

SADSJ

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Desastre é um evento de causa natural e/ou tecnológica que afeta a normalidade do funcionamento social e, por extensão, provoca danos e prejuízos à sociedade, afetando a economia, ecossistemas, estrutura básica e desenvolvimento humano. Por instalação indesejável entende-se que essa instalação deve-se localizar, de preferência, o mais distante possível das populações, assim, em casos de desastres, deve ocorrer o menor dano possível. Neste artigo, decidiu-se abordar a localização de um aterro sanitário. Deste modo, apresenta-se, de forma resumida, a aplicação de um método de apoio à tomada de decisão com múltiplos critérios (Analytic Hierarch Process – AHP) para definir a melhor localização para um aterro sanitário, no contexto da gestão de desastres, no município de Maringá. A área dada como prioritária teve um destaque muito maior que as outras, recebendo quase metade do peso total, dessa forma deve ser extremamente priorizada para receber a instalação.

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Section: Problema De Localizaçãounclassified

Localização De Instalações Indesejáveis No Contexto Da Gestão De Desastres

Calazans¹,

Samed²

2018

SADSJ

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“…Different from the flow-based model, the spatial-based model was studied in [24][25][26][27][28][29][30] for optimizing the locations of EVCSs. Hakimi [24] developed the p-median model (PMM) to minimize the overall distance between demand and service facilities.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging

Guo,

Zhang,

et al. 2023

IET Electrical Systems in Transportation

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Electric vehicle charging stations (EVCSs) are important infrastructures to support sustainable development of electric vehicles (EVs), by providing convenient, rapid charging services. Therefore, the planning of electric vehicle charging network (EVCN) has attracted wide interest from both industry and academia. In this paper, a multiobjective planning model for EVCN is developed, where a fixed number of EVCSs are planned in the traffic network (TN) to achieve two objectives, i.e., minimizing both average travel distance for charging (TDfC) of EVs and investment costs of EVCN. According to the random characteristics of EVs’ TDfC, its constraint is presented as a chance constraint in the developed EVCN planning model. The nondominated sorting genetic Algorithm II with the constraint domination principle (NSGA-II-CDP) is customized to solve the developed multiobjective EVCN planning model, by designing a special coding scheme, a crossover operator, and a mutation operator. Then, a maximum gradient principle of investment revenue is designed to select the optimal planning strategy from the Pareto-optimal solution set, when taking the investment return ratio as primary consideration. A 25-node TN is used to justify the effectiveness of the developed methodology.

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“…The validity of these models is verified using various datasets. Colombo et al (2016) present a multimode generalisation of the MCLP, which is achieved by combining two greedy algorithms. Paul et al (2017) formulate a multi-objective hierarchical extension of the MCLP that seeks to maximise the coverage of the population within a rapid response window while minimising modifications to the existing structure.…”

Section: Introductionmentioning

confidence: 99%

Maximal covering location problem of smart recycling infrastructure for recyclable waste in an uncertain environment

2020

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To incentivise citizens to return recyclable waste (RW) through formal recycling channels, the Chinese government has introduced smart recycling facilities for RW. To maximise the satisfaction of citizens’ demand for returning RW, the proper arrangement of recyclable facilities is a problem worth studying in cases in which there is a lack of data on the citizens’ behaviour. Thus, to help government decision-makers rationally arrange smart recycling facilities, this paper discusses how to properly allocate the recycling infrastructure to cover the maximum demand with a limited number of smart recycling facilities in an uncertain environment. According to the uncertainty theory, the service cost is taken as an uncertain variable. Then, an uncertain maximal covering location problem model and an extended uncertain maximal covering location problem model are constructed, and solution procedures of the two models are provided. The effectiveness of the proposed mathematical formulations and solution procedures were validated through two application cases.

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The multimode covering location problem

Cited by 23 publications

References 24 publications

Localização De Instalações Indesejáveis No Contexto Da Gestão De Desastres

Localização De Instalações Indesejáveis No Contexto Da Gestão De Desastres

Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging

Maximal covering location problem of smart recycling infrastructure for recyclable waste in an uncertain environment

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