An improved algorithm for the distance constrainedp-center location problem with mutual communication on tree networks

Networks ◽  
2004 ◽  
Vol 44 (1) ◽  
pp. 38-40 ◽  
Author(s):  
Arie Tamir
Keyword(s):  
Location Problem ◽  
Tree Networks ◽  
Center Location ◽  
Mutual Communication ◽  
Improved Algorithm

scholarly journals A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 853
Author(s):  
Jesús Sánchez-Oro ◽  
Ana D. López-Sánchez ◽  
Anna Martínez-Gavara ◽  
Alfredo G. Hernández-Díaz ◽  
Abraham Duarte
Keyword(s):  
Location Problem ◽  
State Of The Art ◽  
Path Relinking ◽  
Multiobjective Evolutionary Algorithms ◽  
Demand Point ◽  
High Quality ◽  
Nondominated Solutions ◽  
Center Location ◽  
Strategic Oscillation ◽  
N Demand

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.

The cardinality constrained inverse center location problems on tree networks with edge length augmentation

2021 ◽  
Vol 865 ◽  
pp. 12-33
Author(s):  
Mehran Hasanzadeh ◽  
Behrooz Alizadeh ◽  
Fahimeh Baroughi
Keyword(s):  
Edge Length ◽  
Location Problems ◽  
Tree Networks ◽  
Center Location

scholarly journals A Hybridization of Cuckoo Search and Differential Evolution for the Logistics Distribution Center Location Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Rui Chi ◽  
Yixin Su ◽  
Zhijian Qu ◽  
Xuexin Chi
Keyword(s):  
Differential Evolution ◽  
Optimization Algorithm ◽  
Location Problem ◽  
Cuckoo Search ◽  
Distribution Center ◽  
Metaheuristic Algorithms ◽  
Logistics Distribution ◽  
Center Location ◽  
Mutation Operation ◽  
Distribution Center Location

The location selection of logistics distribution centers is a crucial issue in the modern urban logistics system. In order to achieve a more reasonable solution, an effective optimization algorithm is indispensable. In this paper, a new hybrid optimization algorithm named cuckoo search-differential evolution (CSDE) is proposed for logistics distribution center location problem. Differential evolution (DE) is incorporated into cuckoo search (CS) to improve the local searching ability of the algorithm. The CSDE evolves with a coevolutionary mechanism, which combines the Lévy flight of CS with the mutation operation of DE to generate solutions. In addition, the mutation operation of DE is modified dynamically. The mutation operation of DE varies under different searching stages. The proposed CSDE algorithm is tested on 10 benchmarking functions and applied in solving a logistics distribution center location problem. The performance of the CSDE is compared with several metaheuristic algorithms via the best solution, mean solution, and convergence speed. Experimental results show that CSDE performs better than or equal to CS, ICS, and some other metaheuristic algorithms, which reveals that the proposed CSDE is an effective and competitive algorithm for solving the logistics distribution center location problem.

An Improved Algorithm for the Multi-Commodity Location Problem

1981 ◽  
Vol 32 (2) ◽  
pp. 143 ◽  
Author(s):  
Alan W. Neebe ◽  
Basheer M. Khumawala
Keyword(s):  
Location Problem ◽  
Improved Algorithm
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