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Tua Halomoan Harahap,Ngakan Ketut Acwin Dwijendra,Sulieman Ibraheem Shelash Al-Hawary,A. Heri Iswanto,Noor Mohammed Ahmed,Yousra Mahdi Hasan,Saad Ghazi Talib,Purnima Chaudhary,Yasser Fakri Mustafa 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.3
The traveling salesman problem is one of the most well-known hybrid optimization problems. It is one of the (NP-complete) problems that its various applications have theoretically and operationally attracted the attention of re-searchers. Given that the existing optimization methods to solve such problems include many variables and constraints and reduce their practical efficiency in solving problems with larger dimensions, we have seen the use of algorithms in recent decades. In this research, after determining a linear programming model for the asylum seeker problem with asymmetric distances and solving it in Lingo software, I used two ant cloning algorithms and a forbidden search algorithm to solve the problem in large dimensions. By adjusting the parameters of the two algorithms using the Taguchi method to prove the efficiency of the two algorithms, we compared their results by solving the linear programming model in small-dimensional problems. Then, to compare the results and execution time of the two algorithms, we solved the problem in medium and large dimensions.
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.