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Application of Forest Optimization Algorithm for the Resource Constraint Project Scheduling
Anik Yuesti,Rizqy Amalia Putri,Hussein Tuama Hazim,Oleg N. Polukhin,Hendrixon,Israr AHMAD,Tzu-Chia Chen,Vo Hoang Ca,Huynh Tan Hoi,Surendar Aravindhan 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
Project scheduling is one of the most complex yet important issues in project-based planning. Scheduling is a topic that has entered the project from the production space and has been considered by many researchers in recent years. This problem has always faced many challenges due to its complex limitations in the real world. One of these issues is resource scheduling, known in optimization as the RCPSP problem. The study's main aim is to investigate the applica-tion of a forest optimization algorithm for resource constraint project scheduling. In this research, the RCPSP problem is optimized. A mathematical model is then proposed and then optimized using meteorological algorithms for forest optimization and refrigeration simulation. A hybrid meta-algorithm has also been developed for this document. Examination and comparisons of this algorithm show that the proposed method has the necessary efficiency both in terms of speed and quality of solutions.
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.