A hierarchical location model for public facility planning

Teixeira, João; Antunes, António Pais

doi:10.1016/j.ejor.2006.12.027

Cited by 130 publications

(67 citation statements)

References 25 publications

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“…Alcada-Almeida et al, (2009)designed a Gaussian diffusion model for optimal configuration of multi-objective spatial locationby using mixed integer and multi-objective planning. Teixeira and Antunes(2008) introduced a discrete rating configuration model for public service facility location and validated the effectiveness of the model through a school network planning case. Jing and Jin (2007) proposed that the community planning should start from the city's perspective and aim for interaction with the city and constructed the community design principle of interaction with the city.…”

Section: Aims and Backgroundmentioning

confidence: 99%

Study on Optimal Spatial Configuration of Indemnificatory Community Public Service Facility Based on Modified MOGA

2017

Revista de la Facultad de Ingeniería

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Due to the diversity of its objectives, the optimal spatial configuration process of public service facilities in indemnificatory communities is a multi-objective decision issue. As for the study on optimization for spatial configuration of indemnificatory community public service facility, it is important to find an objective, reasonable and effective method that can address multi-objective decision-making challenges. The method is also the foundation for achieving the effect of indemnification and building a harmonious society. Based on the overall objectives of "resource efficiency" and "maximum benefits", this paper builds the modified Multi-objective Genetic Algorithm (MOGA) model for optimizing spatial configuration of indemnificatory community public service facility, conducts an empirical simulation based on the case of the New Jiangqiao City in Jiading District of Shanghai, with the purpose of introducing the optimal spatial configuration solution for public service facilities. Compared with the ordinary GA-based results, the optimal spatial configuration of public service facilities based on modified MOGA is more reasonable and compact. The model improves the configuration theory for public service facilities in indemnificatory communities, which is of substantial theoretical and practical significance for creating more scientific and reasonable configuration of public service facilities in indemnificatory communities.Keywords:indemnificatory community;public service facility; Multi-objective Genetic Algorithm (MOGA), spatial configuration optimization AIMS AND BACKGROUNDPublic service facility configuration is essentially a complicated multi-objective non-linear dynamic optimization decision-making issue. On the one hand, the configuration process must take into account the effects of various factors such as the location, accessibility and fairness of the public facilities as well as the interaction and interconnection with one another. On the other hand, during the multi-objective optimization for the configuration of public service facilities, the sub-objectives to be optimized simultaneously usually conflict with one another. The key to solving the optimization problem of spatial configuration of public service facilities lies in finding an objective and quantified balance solution (i.e. the Pareto optimal set) under the effects of multiple factors and during the multi-objective optimization.Current researches on the public service facility configuration mainly focus on the subjects of location, accessibility and fairness of facilities. For example, the study on location of public service facilities focuses mainly on their location optimization. Alcada-Almeida et al., (2009)designed a Gaussian diffusion model for optimal configuration of multi-objective spatial locationby using mixed integer and multi-objective planning. Teixeira and Antunes(2008) introduced a discrete rating configuration model for public service facility location and validated the effectiveness of the model through a scho...

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Section: Aims and Backgroundmentioning

confidence: 99%

Study on Optimal Spatial Configuration of Indemnificatory Community Public Service Facility Based on Modified MOGA

2017

Revista de la Facultad de Ingeniería

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“…Hierarchical models are problems in which the upper level and lower level facilities are considered together [15]. Mestre et al [16], Farahani et al [17] and Teixeira and Antunes [18] can be examined as examples of hierarchical models in healthcare services. A summary of the literature related to the single-level facility location-allocation models are given in Table 2.…”

Section: Location-allocation Models On Healthcare Servicesmentioning

confidence: 99%

“…Kariv and Hakimi [48] proved that the problem is a combinatorial NP-Hard problem. The formulation of the P-median problem is as follows [18]: Decision variables: y k = 1, if potential warehouse k is opened (∀k ∈ K); 0 otherwise x ik = 1, if customer i is assigned to potential warehouse k (∀i ∈ I, ∀k ∈ K); 0 otherwise Objective function: (4) is to minimize total costs. Constraint (5) provides the assignment of each customer to a warehouse, while Constraint (6) provides the assignment of customers to the opened warehouses Constraint (7) determines the number of warehouses which should be opened.…”

Section: P-median Problemmentioning

confidence: 99%

Optimizing the location-allocation problem of pharmacy warehouses: A case study in Gaziantep

Özceylan

Uslu

Erbaş³

et al. 2017

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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It is a known fact that basic health care services cannot reach the majority of the population due to poor geographical accessibility. Unless quantitative locationallocation models and geographic information systems (GIS) are used, the final decision may be made on pragmatic considerations which can result far from optimal. In this paper, current and possible (or potential) new locations of pharmacy warehouses in Gaziantep are investigated to provide optimal distribution of hospitals and pharmacies. To do so, first of all, geographic information of 10 current and 10 potential pharmacy warehouses, 231 pharmacies and 29 hospitals are gathered using GIS. Second, a set covering mathematical model is handled to determine coverage capability of current and potential pharmacy warehouses and minimize the number of warehouses to be opened. Finally, P-center and P-median mathematical models are applied to open potential warehouses and to assign pharmacies & hospitals to the opened warehouses so that the total distance and the demand's longest distance to the source are minimized. Developed integer programming (IP) models and GIS software are compared with on a case study. Computational experiments prove that our approach can find new potential pharmacy warehouses which cover wider areas than current warehouses to service pharmacies and hospitals in the city.

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“…This layout failed to consider urban and rural public transport terminal as a whole and was unable to guarantee optimal transportation cost. Existing researches on multi-level hub location primarily focus on facility hierarchical locations, such as production-distribution systems; 9 express delivery services systems; 10 hospitals, schools, and other public service facilities; 11,12 solid waste management systems; 13 and city emergency facilities. 14 The majority of studies take the standpoint of management features and do not consider the use of a hub-and-spoke network structure.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical hub location model and hybrid algorithm for integration of urban and rural public transport

Zhong

Juan

Zong

et al. 2018

International Journal of Distributed Sensor Networks

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Integration of urban and rural infrastructure is critical to integrating urban and rural public transport. A public transport hub is an important element of infrastructure, and it is the key facilities that serve as transferring points between cities and towns. The location of hub is related to the convenience of travel for urban and rural residents and the closeness of economic interactions between urban and rural areas. In this article, considering the background of the integration of urban and rural public transport, from the perspective of public transport hubs in urban and central town, a multi-level hub-and-spoke network is designed, and the location of integration of urban and rural public transport hub is determined. Based on the connection associated with central towns and the capacity constraints of hubs and to achieve the minimum total cost, this article proposes a mixed-integer programming model that employs a genetic and tabu search hybrid optimization algorithm to validate and analyze, which used the urban and rural public transport data from a specified area of Shandong province in China. The results indicate that the model can simultaneously determine locations for hubs in cities and central towns while minimizing total cost. The hub capacity constraint significantly influences the location of two-level hubs. The hub capacity constraint in the model can reduce the transportation cost for an entire network and optimize the transportation network. This study on urban and rural public transport hub location in a huband-spoke network not only reduces the transportation cost of the network but also completes and supplements the location theory of integration of urban and rural public transport.

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A hierarchical location model for public facility planning

Cited by 130 publications

References 25 publications

Study on Optimal Spatial Configuration of Indemnificatory Community Public Service Facility Based on Modified MOGA

Study on Optimal Spatial Configuration of Indemnificatory Community Public Service Facility Based on Modified MOGA

Optimizing the location-allocation problem of pharmacy warehouses: A case study in Gaziantep

Hierarchical hub location model and hybrid algorithm for integration of urban and rural public transport

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