Optimal facility location problem on polyhedral terrains using descending paths

Dutta, Binayak; Karmakar, Arindam; Roy, Sasanka

doi:10.1016/j.tcs.2020.09.037

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…In another context, [5] studied the problem of Descending Facility Location (DFL) on the surface of a triangulated terrain. Given a set of n demand points on the surface of a triangulated terrain, their goal is to find a set F (of points), of minimum cardinality, on the surface of the terrain such that for each demand point, there exists a path down from at least one facility to d. They presented a time-based algorithm to solve the DFL problem, where m is the number of vertices in the triangulated terrain.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Multi-objective Optimization Approach for Warehouses Location Problem

Mankour,

Yachba

2023

Preprint

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Many recent studies show that supply chain design positively impacts logistics performance and cost. Companies today are forced to make many types of decisions to ensure their medium- and long-term survival. Many issues are raised by this practice, such as the optimization of the supply chain. Our work is mainly focused on the research of distribution of products to customers. This network is made up of customers and warehouses. We suggest in this study a new method for selecting potential warehouses based on the particle swarm algorithm, which is a metaheuristic method. The proposed method, HWS-MOPSO (Hybrid Warehouse Selection Multi-Objective Particle Swarm Optimization), is a hybrid method based on two essential methods. The first step is to gather nearby customers using an unsupervised learning method. The second step is choosing the best warehouse location. This method makes it easier to perform three objectives. Finally, the analysis of its performance is carried out in a set of customers and warehouses. The test results demonstrate that the suggested method is effective and can select several warehouses (variables) and maintain the best cost, distance, and delay.

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Section: Related Workmentioning

confidence: 99%

A Hybrid Multi-objective Optimization Approach for Warehouses Location Problem

Mankour,

Yachba

2023

Preprint

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Cluster Nested Loop k-Farthest Neighbor Join Algorithm for Spatial Networks

Cho

2022

IJGI

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This paper considers k-farthest neighbor (kFN) join queries in spatial networks where the distance between two points is the length of the shortest path connecting them. Given a positive integer k, a set of query points Q, and a set of data points P, the kFN join query retrieves the k data points farthest from each query point in Q. There are many real-life applications using kFN join queries, including artificial intelligence, computational geometry, information retrieval, and pattern recognition. However, the solutions based on the Euclidean distance or nearest neighbor search are not suitable for our purpose due to the difference in the problem definition. Therefore, this paper proposes a cluster nested loop join (CNLJ) algorithm, which clusters query points (data points) into query clusters (data clusters) and reduces the number of kFN queries required to perform the kFN join. An empirical study was performed using real-life roadmaps to confirm the superiority and scalability of the CNLJ algorithm compared to the conventional solutions in various conditions.

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Comparative Study for Facilities Location Problem in Supply Chain Design

Mankour

Yachba

2022

International Journal of Swarm Intelligence Research

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The interest in supply chains has increased in the last few years. The supply chain optimization aims to reduce the delays and costs generated between suppliers and customers. The researchers focus primarily on the supply chain design to transport products to clients. This paper attempts to find an optimal warehouse location using a metaheuristic method. The goal is to select the optimum warehouse location. FLP-GA (Facility Location Problem - Genetic Algorithms) is the proposed approach based on genetic algorithms that reduce the number of warehouses to be opened, the overall costs, and the distances between them from a set of customers and candidate warehouses. The authors compared the approach with three other methods. This approach can select a reduced number of warehouses with minimal cost.

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Optimal facility location problem on polyhedral terrains using descending paths

Cited by 3 publications

References 8 publications

A Hybrid Multi-objective Optimization Approach for Warehouses Location Problem

A Hybrid Multi-objective Optimization Approach for Warehouses Location Problem

Cluster Nested Loop k-Farthest Neighbor Join Algorithm for Spatial Networks

Comparative Study for Facilities Location Problem in Supply Chain Design

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