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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.
Mushroom Supply Chain Network Design Using Robust Optimization Approach under Uncertainty
Sen Xie,Akbar Formonov,Abdulqader Abdulrahman Thapit,Mohammed Hayder Alshalal,Mostafa Kamel Shakir Obeis,R. Sivaraman,Abdullah Hasan Jabbar,Purnima Chaudhary,Yasser Fakri Mustafa 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.3
Nowadays, attention to sustainable food security and health and the incentive to increase revenue, has led many governments and policymakers to pay special attention to the effective performance of the agricultural supply chain. The positive effects of paying attention to agricultural supply chain management can be easily seen in job creation in urban and rural areas, easy access to the market for agricultural retailers and the appropriate relationship between small and medium businesses. This study examines the complete supply chain network of agricultural products (mushroom industry) in uncertain conditions. The model is presented in the form of two general objectives; the first objective refers to minimizing network costs, and the second objective to minimizing network environmental pollutants. Also, the proposed model is in uncertain conditions, and to overcome the uncertainty model, the optimization approach has been used. Finally, due to the multi-objective nature of the proposed model, the reinforced epsilon-constraint solution approach is used. Simulated data has been utilized to validate the proposed robust model. Given the results, the recycling rate of the consumed compost was above 0.4, demonstrating that applying a closed-loop supply chain network is logical, and establishing a recycling center could be economically justified.
Iskandar MUDA,R. Sivaraman,Sulieman Ibraheem Shelash Al-Hawary,Untung Rahardja,Rusul S. Bader,Deni Kadarsyah,Karrar Shareef Mohsen,Abdullah Hasan Jabbar,Purnima Chaudhary 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.3
In this research, the location of hubs in computer networks is investigated using the whale optimization algorithm. The problem of locating hubs in computer networks is an optimization problem and requires the definition of a suitable fit function. Therefore, the total data transfer time and the cost of creating hubs is used as a fit function. Capacitive hubs increase network availability because hubs have more response capacity than the number of node requests connected to the hubs. In hub location issues, the study seeks to connect the nodes to the nearest hub and create a computer network with the least cost of connecting the nodes to the hubs. The present study attempts to reduce disruptions in computer networks as a research innovation. Therefore, by using the whale optimization algorithm and solving the model with its help, the effective factors that affect computer network disruptions and examining the effect of each are identified. Given the results, the model’s reaction in terms of time and cost led to an increase in temporal and cost parameters.
Multi-objective Mathematical Modeling for Scheduling Machines in Parallel with Batch Processors
Evy Segarawati Ampry,Aan Komariah,Dedy Achmad Kurniady,Muhammad Rafiq,Asep Priatna,Muneam Hussein Ali,Haydar Abdulameer Marhoon,Lakshmi Thangavelu,Purnima Chaudhary 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
In this paper, the problem of scheduling the production of unrelated parallel machines to simultaneously minimize the goals of production time span, early and late fines, and the cost of purchasing machines is investigated, and a two-objective mathematical model is considered considering clearance and preparation times and limit capacity. Due to faster and cheaper operations with batch processors and increasing the efficiency of operating systems, all machines are batch processors. Initially, the model is coded and executed using the exact method in GAMS software. Due to the hard-NP nature and complex nature of the problem, a multi-objective meta-heuristic algorithm based on the coordination search method is proposed and designed. Then Taguchi method is used to find the best level for the algorithm parameters, and two examples of problems in different dimensions of tasks and machines are presented and solved by this proposed algorithm. The results of the calculations show the efficiency of this algorithm to generate more solutions at a much lower solution time.
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.