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Route Optimization of Container Ships Using Differential Evolution and Gray Wolf Optimization
Juhriyansyah Dalle,Paitoon Chetthamrongchai,Gunawan Widjaja,Egor Dudukalov,A. Heri Iswanto,Elena Sergeevna Sergushina 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
Container ships carry most of the world's cargo volume. Hence, Maritime transportation forms the backbone of the world merchandise trade. Today, with the advancement of shipbuilding technology and the increasing frequency of maritime transport, determining the optimal route for container ships has become more and more important for ship-ping lines and port managers. Accordingly, in the present study, we intend to investigate the ship routing problem us-ing a mixed integer linear mathematical programming model. In order to solve the proposed model, we have used the meta-heuristic algorithms of differential evolution and gray wolf optimization in MATLAB software. In the end, it was shown that the proposed mathematical model and solution approaches can assist ship operators and terminal managers in making reasonable optimization decisions.
Benjarut Chaimankong,Paitoon Chetthamrongchai 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
One of the effective ways to ensure the reliability of the product sold is to consider service and warranty contracts. Important decision variables in warranty policies include determining the optimal warranty period and the optimal number of maintenance activities. In this research, a model has been developed with the aim of achieving the lowest expected cost rate in the life of the device and the appropriate reliability by performing the optimal number of preventive maintenance measures. The warranty policy in this study is renewable in two dimensions, in which two dimensions of repair time and failure time are considered. Any damage leading to repair is done free of charge by the manufacturer and damage leading to replacement is done jointly between the manufacturer and the consumer by agreement. As a result, two algorithms of Genetic and Imperialist Competitive Algorithm have been developed to solve the model and have been compared with numerical example solving. Furthermore, the shelfs life of the system and the number of optimal repair and maintenance measures for maintaining reliability required by the buyer were obtained.
Optimizing the Issue of Blood Supply Chain Network Design with a Reliability Approach
Anik Yuesti,Paitoon Chetthamrongchai,Alim Al Ayub Ahmed,Vera Anitra,Surendar Aravindhan,Ravil Akhmadeev,Dedy Achmad Kurniady,Clara Neltje Meini Rotinsulu,M. Kavitha 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
Supply chain network design of a product is one of the primary and strategic measures in supply chain management that plays a vital role in supply chain performance. Since blood is a special commodity and has no substitute, supply chain management and optimization have a special place among researchers. In this research, for the first time, a two-objective nonlinear mixed integer model is presented to help make strategic and operational decisions in the blood supply chain. The first objective function is related to cost minimization and the second objective function is related to supply chain reliability maximization, which is considered as a series-parallel system. To check the validity of the model, a numerical example is solved using GAMS software, then using MOPSO meta-heuristic algorithm, the model is solved in larger dimensions and while comparing the performance criteria of multi-objective algorithms, the results are reviewed.
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.
Optimization of the Location, Inventory and Routing of Capacity Vehicles with Interval Uncertainty
Trisnowati Josiah,Arif Suhada,Paitoon Chetthamrongchai,Heppy Purbasari,Hussein Tuama Hazim,Abdul Aziz Purnomo Shidiq,Tri Harsini Wahyuningsih,Irina Yuryevna Potashova,Surendar Aravindhan 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
In today's industrial world, manufacturing units are trying to reduce their costs by properly locating the warehouses they need as well as routing vehicles to transport manufactured goods to these warehouses. In fact, the inventory-routing location model is an integrated supply chain design model that simultaneously optimizes location, inventory, and routing decisions. The purpose of this paper is to provide an integrated model for locating warehouses, allocating stores to warehouses, and finding inventory at the end of the course and routing decisions such as determining the routes of vehicles starting from a distribution center opened to serve customers. Eventually return to the same distribution center; in such a way that the total system costs are minimized. The model is formulated as a mixed integer linear programming model (MILP) and a robust optimization approach has been used to optimize the problem under uncertainty conditions. To solve the model and demonstrate its feasibility, GAMS software and to compare the results of the software MATLAB is used.
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.