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Application of Experimental Design in Optimizing Fuel Station Queuing System
Ngakan Ketut Acwin Dwijendra,Irina Vaslavskaya,Natalia Vladimirovna Skvortsova,Tatyana Pavlovna Rakhlis,Untung Rahardja,Muneam Hussein Ali,A. Heri Iswanto,Lakshmi Thangavelu,Mustafa M. Kadhim 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
This paper investigates the 224 active fuel stations to find thee optimal distribution system. This research aims to de-sign a model based on simulation to optimize the queuing system and fuel station sales. This study combines simula-tions and experimental design techniques that lead to a predictable and experimental model for optimizing the system and performance of a fuel station by considering two perspectives of queue length and sales rate. Initially, the fuel station was simulated using Arena software. After simulating the fuel station system, we tried to optimize the station's performance using the design of experiments and response level methodology (RSM). The results obtained from the optimal model indicate that the results lead to improved system performance. The fuel station queue is studied
Multi Project Scheduling and Material Planning Using Lagrangian Relaxation Algorithm
Alim Al Ayub Ahmed,Ngakan Ketut Acwin Dwijendra,Naresh Babu Bynagari,A. K. Modenov,M. Kavitha,Egor Dudukalov 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
Resource-constrained project scheduling is one of the well-known problems in project management. There are many cases where the appropriate schedule was determined first and material ordering plan was decided considering the given schedule. This approach ignores the interactions between these decisions. The integration of project scheduling, material procurement, and production planning of non-renewable resources leads to the coordination of project im-plementation and supplying resources. This coordination reduces total costs, including operating activities, produc-tion, ordering, holding, and penalty costs for late project completion. In addition to, there are many organizations that implement the multi project at the same time and decisions are made in a multi project environment. In this paper, a mixed integer programming model is presented for the resource-constrained multi-project scheduling problem and material ordering and production planning. Due to the application of Lagrangian relaxation algorithm in solving com-plex problems, this algorithm has been used to solve the proposed mathematical model. To evaluate the performance of the proposed model and solution method, a set of sample examples is solved and the numerical results are given. The findings of this paper show the good performance of the model and the solution method and can provide managerial insights for project managers and resource suppliers.
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.
A Multi-Objective Mathematical Model for the Population-Based Transportation Network Planning
Supat Chupradit,Mohammad A. Tashtoush,Mohammed Yousif Oudah Al-Muttar,Trias Mahmudiono,Ngakan Ketut Acwin Dwijendra,Purnima Chaudhary,Muneam Hussein Ali,Ahmed Alkhayyat,Dr. Sutarto 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
The current article introduces a three-objective model for the problem of location, allocation, and routing, taking into account the travel times depending on the population on the route. Objective functions include minimizing the total network transit time, maximizing travel attractiveness for travel applicants, and balanced allocation of travel appli-cants to each service area. In this research, a general form of the proposed three-objective mathematical planning model is formulated. The proposed model seeks to select a suitable place or places as places of service, allocate people or vehicles in each area to these places and determine the transportation route of each person or vehicle in each area to reach the service provider in question. Getting a direct impact of random factors and population flow on the random travel times of each bow so that all three goals are met simultaneously. The cuckoo optimization algorithm is developed to solve this model. A sample problem is also examined to show the validity and behavior of the proposed model. The numerical results indicate the high performance of the cuckoo optimization algorithm.