scholarly journals The Capacitated Location-Allocation Problem Using the VAOMP (Vector Assignment Ordered Median Problem) Unified Approach in GIS (Geospatial Information Systam)

2020 ◽  
Vol 10 (23) ◽  
pp. 8505
Author(s):  
Alireza Vafaeinejad ◽  
Samira Bolouri ◽  
Ali Asghar Alesheikh ◽  
Mahdi Panahi ◽  
Chang-Wook Lee
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Unified Approach ◽  
Exact Methods ◽  
Median Problem ◽  
Geospatial Information ◽  
Location Allocation ◽  
Ordered Median ◽  
Allocation Problems ◽  
Fire Stations

The Vector Assignment Ordered Median Problem (VAOMP) is a new unified approach for location-allocation problems, which are one of the most important forms of applied analysis in GIS (Geospatial Information System). Solving location-allocation problems with exact methods is difficult and time-consuming, especially when the number of objectives and criteria increases. One of the most important criteria in location-allocation problems is the capacity of facilities. Firstly, this study develops a new VAOMP approach by including capacity as a criterion, resulting in a new model known as VAOCMP (Vector Assignment Ordered Capacitated Median Problem). Then secondly, the results of applying VAOMP, in scenario 1, and VAOCMP, in scenario 2, for the location-allocation of fire stations in Tehran, with the objective of minimizing the arrival time of fire engines to an incident site to no more than 5 min, are examined using both the Tabu Search and Simulated Annealing algorithms in GIS. The results of scenario 1 show that 52,840 demands were unable to be served with 10 existing stations. In scenario 2, given that each facility could not accept demand above its capacity, the number of demands without service increased to 59,080, revealing that the number of stations in the study area is insufficient. Adding 35 candidate stations and performing relocation-reallocation revealed that at least three other stations are needed for optimal service. Thirdly, and finally, the VAOMP and VAOCMP were implemented in a modest size problem. The implementation results for both algorithms showed that the Tabu Search algorithm performed more effectively.

scholarly journals INVESTIGATING THE EFFECT OF CAPACITY CRITERION ON THE OPTIMAL ALLOCATION OF EMERGENCY FACILITIES IN GIS ENVIRONMENT

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 211-217
Author(s):  
S. Bolouri ◽  
A. Vafaeinejad ◽  
A. Alesheikh ◽  
H. Aghamohammadi
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimal Allocation ◽  
Specific Capacity ◽  
Median Problem ◽  
Location Allocation ◽  
Ordered Median ◽  
Fire Stations ◽  
Gis Environment ◽  
Location Allocation Problem

Abstract. Location-allocation analysis is one of the most GIS useful analysis, especially in allocating demands to facilities. One of these facilities is the fire stations, which the correct locations and optimal demand allocations to those have most importance. Each facility has a specific capacity that should be considered in locating the facilities and allocating the demand to those. In recent years, the use of unified models in solving allocation problems is too common because these models can solve a variety of problems, but in most of these models, the capacity criterion for facilities has been ignored. The present study tries to investigate the location-allocation problem of the fire stations with the aid of two Tabu and Genetic algorithms with the goal of maximizing the coverage using the (Vector Assignment Ordered Median Problem) VAOMP model, taking into account the capacity criterion and regardless of it. The results of using two algorithms in problem-solving show that the Genetic algorithm produces better quality solutions over a shorter time. Also, considering the capacity criterion that brings the problem closer to real-world space, in the study area, 59,640 demands will not be covered by any station within a 5-minute radius and will be highly vulnerable to potential hazards. Also, by adding 3 stations to the existing stations and re-allocating, the average of allocated demands with the help of Genetic was 93.39% and 92.74% for the Tabu algorithm. So it is necessary to consider the capacity of the facilities for optimal services.

scholarly journals Penyelesaian Masalah TSP Pada Rute Kunjungan ATM Dengan Pendekatan Heuristik (Tabu Search)

2017 ◽  
Vol 2 (1) ◽  
pp. 13
Author(s):  
Jhon Pontas Simbolon ◽  
Muhammad Zarlis
Keyword(s):  
Tabu Search ◽  
Minimum Distance ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Heuristic Method ◽  
Search Process ◽  
Local Optimum ◽  
Heuristic Methods ◽  
Exact Methods

Determination of optimum route is a problem that can be found in a variety of activities. Principal of the problem is how to organize the trip so the distance is the minimum distance that the optimum is best found on a map or graph. There are many algorithms available to solve them. Algorithm is divided into two parts, the exact methods and heuristic methods. Heuristic method is considered the best method because it can work quickly. Tabu search is a heuristic method that is often used in solving optimization problems. The algorithm works by improving a solution by using memory to avoid that the search process does not get stuck at a local optimum value by rejecting new solutions that may be in memory (taboo) so that the new solution will be more dispersed. The author will implement a tabu search algorithm to provide a better alternative solution to solve the problems of the effectiveness of the distribution of charging money at the ATM machine.

Determination of Optimal Public Transportation Routes Using Firefly and Tabu Search Algorithms

2020 ◽  
Vol 4 (5) ◽  
pp. 884-891
Author(s):  
Salwa Salsabila Mansur ◽  
Sri Widowati ◽  
Mahmud Imrona
Keyword(s):  
Tabu Search ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Search Algorithm ◽  
Urban Transportation ◽  
The Public ◽  
Comparison Results ◽  
Congestion Problems ◽  
Transportation Routes

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

Parallel iterative solution-based tabu search for the obnoxious p-median problem

2021 ◽  
Vol 127 ◽  
pp. 105155
Author(s):  
Jian Chang ◽  
Lifang Wang ◽  
Jin-Kao Hao ◽  
Yang Wang
Keyword(s):  
Tabu Search ◽  
Iterative Solution ◽  
Median Problem ◽  
Parallel Iterative
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