July 22, 2024
Khodakaram Salimifard

Khodakaram Salimifard

Academic Rank: Associate professor
Address: Industrial Management Department, Business & Economics School, Persian Gulf University, Bushehr 75169
Degree: Ph.D in Operations Research
Phone: 07731222118
Faculty: School of Business and Economics

Research

Title
Scheduling Staff Training Courses Using Particle Swarm Optimization Algorithm
Type Thesis
Keywords
جدول بندي زماني، زمانبندي، آموزش كاركنان، برنامه‏ريزي عدد صحيح، الگوريتم بهينه سازي ازدحام ذرات
Researchers sezad sajad mojahed al mosavie (Student) , Khodakaram Salimifard (Primary advisor) , Ahmad Ghorbanpour (Advisor)

Abstract

Regarding staff training, it can be said that this plays a key role in the development of organizations. Training is a process that human resource management must pay attention to in relation to human resource development. What is important in education is the quality of education and the right program with education or in general, proper and purposeful educational planning. Therefore, this research is related to educational planning for the company under study. The main purpose of this research is educational planning and creating an optimal educational calendar for the company under study. Training planning was done for the employees of the study company, which numbered 700 people, for one month, according to the training needs assessment table. First, according to the previous mathematical models and the conditions of the company, a mathematical model was presented for the research problem. Due to the NP-hard nature of the problem, a particle swarm optimization algorithm was used for optimization. Also, a comprehensive benchmark method was used to optimize the multi-objective research problem. The optimization was performed separately for each of the three problem objectives. Then, using the comprehensive benchmark method and the values of P = 1, p = 2 and p = 3, optimization was performed for the three-objective problem, and from the optimization of each problem, an educational calendar was obtained in which it is specified on which days in each period. And in which class it is held. It was also determined which employees are present in each period, and vacancies were identified for possible periods with optimization. Finally, the results of optimization of all six problems in the form of a decision matrix were proposed to decision makers. According to the results of the problem optimization, more courses can be held than before the optimization. Also, more people participate in the courses and employee satisfaction increases with the convenience of holding the