Probabilistic Tabu Search Algorithm for the Multi-Stage Uncapacitated Facility Location Problem

2001 ◽  
pp. 65-70 ◽  
Author(s):  
Y. A. Kochetov ◽  
E. N. Goncharov
Keyword(s):  
Tabu Search ◽  
Facility Location ◽  
Location Problem ◽  
Search Algorithm ◽  
Facility Location Problem ◽  
Tabu Search Algorithm ◽  
Uncapacitated Facility Location Problem ◽  
Multi Stage

scholarly journals Penerapan Cuckoo Search Algorithm (CSA) untuk Menyelesaikan Uncapacitated Facility Location Problem (UFLP)

2019 ◽  
Vol 1 (1) ◽  
pp. 34
Author(s):  
Asri Bekti Pratiwi ◽  
Nur Faiza ◽  
Edi Edi Winarko
Keyword(s):  
Big Data ◽  
Facility Location ◽  
Customer Service ◽  
Location Problem ◽  
Search Algorithm ◽  
Facility Location Problem ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Small Data ◽  
Uncapacitated Facility Location Problem

The aim of this research is to solve Uncapacitated Facility Location Problem (UFLP) using Cuckoo Search Algorithm (CSA). UFLP involves n locations and facilities to minimize the sum of the fixed setup costs and serving costs of m customers. In this problem, it is assumed that the built facilities have no limitations in serving customers, all request from each customers only require on facility, and one location only provides one facility. The purpose of the UFLP is to minimize the total cost of building facilities and customer service costs. CSA is an algorithm inspired by the parasitic nature of some cuckoo species that lay their eggs in other host birds nests. The Cuckoo Search Algorithm (CSA) application  program for resolving Uncapacitated Facility Location Problems (UFLP) was made by using Borland C ++ programming language implemented in two sample cases namely small data and big data. Small data contains 10 locations and 15 customers, while big data consists 50 locations and 50 customers. From the computational results, it was found that higher number of nests and iterations lead to minimum total costs. Smaller value of pa brought to better solution of UFLP.

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