Hybrid Covering Location Problem: Set Covering and Modular Maximal Covering Location Problem

Alizadeh, Roghayyeh; Nishi, Tatsushi

doi:10.1109/ieem44572.2019.8978601

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…The problem of subsetting a subdomain around a given location or set of points, appears to be similar to several canonical problems treated in the realm of optimization. Among the relevant applications we found the topics of set covering problems [1], shape and object packing problems (both regular and irregular) [2,7,15,19,20,27], location problems [8,16,21,28] and districting problems [10,17,29] to relate very closely to the general aspects of our specific domain subsetting needs. Even though a wide variety of literature was found within the last 7 years concerning the aforementioned applications, in this section we cover only the most relevant papers that explore diverse methods for solving problems directly comparable or applicable to our domain subsetting problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Alizadeh and Nishi [1] proposed to solve a hybrid location problem derived from disaster or emergency relief scenarios, which is a meld between the set covering problem (SCP) and the maximal covering location problem (MCLP). In the SCP, a minimum number of facilities is found such that coverage is maximized to meet the demand; alternatively MCLP tries to maximize the covered demands, using a fixed, given set of facilities.…”

Section: Set Covering Problemsmentioning

confidence: 99%

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Wildfire burn scar encapsulation

2021

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Wildfires burn annually across the United States (US), which threaten those in close proximity to them. Due to drastic alterations of soil properties and to the land surfaces by these fires, risks of flash floods, debris flows, and severe erosion increases for these areas, which can have catastrophic consequences for biota, people and property. Computational tools, such as the WildfireRain algorithm, have been designed and implemented to assess the potential occurrence of debris flows over burn scars. However, in order to efficiently operate these tools, they require independent, non-overlapping buffers around burned areas to be defined, which is not a trivial task. In this paper we consider the problem of efficiently subsetting the conterminous US (CONUS) domain into optimal subdomains around burn scars, aiming to enable domain-wide WildfireRain product outputs to be used for operations by the National Weather Service (NWS). To achieve this, we define the Object Encapsulation Problem, where burn scars are represented by single-cell objects in a gridded domain, and circular buffers must be constructed around them. We propose a Linear Programming (LP) model that solves this problem efficiently. Optimal results produced using this model are presented for both a simplified synthetic data set, as well as for a subset of burn scars produced by severe wildfires in 2012 over the CONUS.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Set Covering Problemsmentioning

confidence: 99%

Wildfire burn scar encapsulation

2021

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“…Some of the Set Covering models include the Location Set Covering Problem (LSCP) (Machado et al, 2021) and p-Median Problem (Doungpan, 2020;Sitepu et al, 2022). LSCP is a problem in the distribution system that aims to find the optimal number of facility locations (Yang et al, 2020;Zhang and Zhang, 2015) so that it can serve all points of demand (Alizadeh and Nishi, 2019;Kocaoglu et al, 2014;Mohri and Haghshenas, 2021). The p-Median problem aims to find the location of the facility so that the p-total cost between each request and the nearest facility is minimized (Özceylan et al, 2017) .…”

Section: Introductionmentioning

confidence: 99%

Formulation of Set Covering Problem Using Myopic Algorithm and Greedy Reduction Algorithm in Determining the Location of Temporary Landfills in Semambu Island Village, Ogan Ilir Regency, South Sumatra

Puspita

Octarina

Hanum

et al. 2023

Sci. Technol. Indones

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This study discusses Set Covering Problem (SCP) in designing the optimal temporary waste disposal site (TWDS) in Semambu Island Village using the Myopic Algorithm (MA) and Greedy Reduction Algorithm (GRA). The analysis was carried out and compared using a maximum distance of 500m and 1000m to get the best solution from two methods. The results of the p Median Problem by LINGO 13.0 software and MA with a maximum distance of 500m show the same TWDS location, namely Working Area (WA) 1, 2, 3, 4, 5, and 6 with the location of the candidate TWDS being at TWDS 2 WA 1, TWDS 1 WA 2, TWDS 2 WA 3, and TWDS 2 WA 5. For 1000m, it will be the location of the candidate’s TWDS being at TWDS 2 WA 1, TWDS WA 2, and TWDS 2 WA 3. Using GRA, results were obtained will be 4 TWDS, namely TWDS 2 Hamlet 1, TWDS 1 Hamlet 2, TWDS 2 Hamlet 3, TWDS 2, Hamlet 5. Then using GRA, 2 solutions are obtained, namely columns 2 and 5 which dominate. Column 2 nomination are Hamlets 1, 2, 3, and 6. Column 5 which dominates will be Hamlets 1, 3, 5, and 6.

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Multi-observation points setting problem based on stepwise maximum viewshed approach

Wang,

Ma,

2024

International Journal of Geographical Information Science

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Hybrid Covering Location Problem: Set Covering and Modular Maximal Covering Location Problem

Cited by 3 publications

References 14 publications

Wildfire burn scar encapsulation

Wildfire burn scar encapsulation

Formulation of Set Covering Problem Using Myopic Algorithm and Greedy Reduction Algorithm in Determining the Location of Temporary Landfills in Semambu Island Village, Ogan Ilir Regency, South Sumatra

Multi-observation points setting problem based on stepwise maximum viewshed approach

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