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A Multi-Objective Optimization Model for Relief Facility Location in Crisis Conditions
Alim Al Ayub Ahmed,Jaenudin,Gunawan Widjaja,John William Grimaldo Guerrero,Mustafa M. Kadhim,Konstantin Kolyazov 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
This research was conducted to study the issue of relief facility location hierarchically by consideration of possible road closure during the crisis conditions, road safety, and arrival time of relief facilities under disaster circumstances. High costs are allocated for facilities deployment in a suitable location to meet the demands of injured people. There-fore, location-allocation of emergency facility should be considered in a way to use them for long-term periods. To this end, the extant research designed a multi-objective optimization model to minimize the pre-disaster costs includ-ing costs of facilities deployment and road use, and to minimize the post-disaster costs such as cost transportation in-network roads. Moreover, the innovative part of the studied model in this research examined the road safety and reduction in time taken to have critical facilities in affected areas. To investigate the functional accuracy of the mathematical model, a numerical example with small dimensions was solved using CPLEX Solver, and required sensitivity analysis was described. As the facility location-allocation is an NP-hard issue, two meta-heuristic algorithms were used to solve numerical representations in real dimensions to examine numerical analyses effectively. Results showed that the dragonfly algorithm had the highest efficiency compared to other developed algorithms. The obtained results can be considered as an efficient managerial tool in management organizations involved in the crisis
Dadang Mohamad,Alim Al Ayub Ahmed,Gunawan Widjaja,Tawfeeq Alghazali,John William Grimaldo Guerrero,Irina Fardeeva,Alireza Hasanzadeh Kalajahi 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
The problem studied in this paper is the p hub center and the network structure is hierarchical and in three levels; where level one is for demand nodes, level two is for hub nodes, and level three is for central hubs. Central hubs have a complete network and hubs in the network have the capacity constraint. Given that the issue under consideration is for the purpose of transporting perishable goods, Such problems are often used in transportation systems in which customer response time is of great importance and sensitivity; Therefore, the objectives of the proposed model are to find the best location for hubs in the network as well as the best allocation of nodes to hubs so that network transportation costs are reduced and the maximum travel time between each pair of origin destination nodes is minimized. To evaluate the model, a numerical example with CAB dataset is introduced and to review and analyze the results, GAMS software with CPLEX solver is used. The results show that the discount coefficient of central hubs compared to the discount coefficient of second level hubs has the greatest impact on the cost of transportation and travel time.
Scheduling for a Container Supply Chain to Minimize Costs Using the Meta-Innovation Approach
Ismail Husein,Arif Suhada,Paitoon Chetthamrongchai,Andrej P. Peressypkin,Anis Siti Nurrohkayati,Vo Hoang Ca,Huynh Tan Hoi,John William Grimaldo Guerrero,M. Kavitha 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard-NP problem and cannot be solved on a large scale with precise methods in a logical time. Therefore, to solve and optimize the model, a meta-innovative algorithm, genetic algorithm, has been used. Also, to increase the effectiveness of the genetic algorithm, the parameters of the algorithm are adjusted using the Taguchi method. Finally, a number of problems have been solved to show the performance of this algorithm and its computational results have been compared with the results obtained from GAMS software.
Scheduling for a Container Supply Chain to Minimize Costs Using the Meta-Innovation Approach
Tua Halomoan Harahap,Hikee Altaee,Paitoon Chetthamrongchai,Andrej P. Peressypkin,Anis Siti Nurrohkayati,Vo Hoang Ca,Huynh Tan Hoi,John William Grimaldo Guerrero,M. Kavitha 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard-NP problem and cannot be solved on a large scale with precise methods in a logical time. Therefore, to solve and optimize the model, a meta-innovative algorithm, a genetic algorithm, has been used. Also, to increase the effectiveness of the genetic algorithm, the parameters of the algorithm are adjusted using the Taguchi method. Finally, a number of problems have been solved to show the performance of this algorithm and its computational results have been compared with the results obtained from GAMS software. The study’s results demonstrate that the efficiency of displacement inside ports and fuel price on the overall costs, the optimal number of ships utilized, and the optimal scheduling table.