“…Bolouri et al from the perspective of spatial justice, examined the condition of fire stations using two algorithms, Simulated Annealing and Tabu Search, using VAOMP in solving location-allocation problem. The results showed that the location of some of the existing facilities for service is not suitable [24].…”
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.
“…Bolouri et al from the perspective of spatial justice, examined the condition of fire stations using two algorithms, Simulated Annealing and Tabu Search, using VAOMP in solving location-allocation problem. The results showed that the location of some of the existing facilities for service is not suitable [24].…”
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.
“…Chukwuma (2019) attended to the bioenergy systems in the Anambra State of Nigeria and located the related facilities using an integrating approach consisting of GIS and location model. Bolouri et al (2020) focused on the green facility location. For this aim, they find the optimum location of the urban facilities by applying the GIS and ordered median problem.…”
PurposeTo avoid sub-optimization in wheat storage centers, one of the most strategic facilities, it is necessary to review and relocate them to be optimized regularly. The present study aims to propose an integrated method using geographic information systems (GISs) and an appropriate weighting algorithm for the relocation of wheat storage facilities.Design/methodology/approachTo achieve the goal mentioned above, sustainability pillars in facility location and relocation are initially developed; afterward, a set of suitable criteria are obtained from various scientific resources. Then, the weight of each sustainable development pillar and its corresponding sub-criteria were identified through utilizing the best–worst method (BWM). By applying the obtained weights in the ArcGIS software package, various geographical layers were designed, and land-use planning, logistics planning and sustainable logistics planning are carried out in the regions. The regions are ranked based on the scores obtained in the processes, and the best regions are selected for sustainable relocation problem.FindingsA case study including 430 regions (counties) in Iran is conducted to evaluate the efficiency of the suggested approach. The study results indicate that Iran possesses a superior state for establishing wheat storage centers in terms of infrastructural and social aspects. Also, it is established that 16% of counties are recognized as sustainable locations for relocating the wheat storage facilities.Research limitations/implicationsThere is no most suitable analysis of the wheat storage facilities, as well as their strategic position in the supply chain, and there is a lack of considering sustainability in wheat storage facility location, despite the particular importance of it to the supply chain.Practical implicationsThis framework is applied in an Iranian wheat-bread supply chain to find the best sustainable facilities. It is noted that this algorithm can be applied in other strategic facilities by minor and some major changes.Originality/valueDecision-makers can apply the proposed methodology to find the best relocation sites for wheat storage facilities as the main part of wheat-bread supply chain in order to prevent sub-optimization and improve the efficiency of their supply chain.
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