A Compromise Programming for Multi-Objective Task Assignment Problem

• Published in: Computers (Basel) Vol. 10; no. 2; p. 15
• Main Authors: Ngo, Son Tung, Jaafar, Jafreezal, Aziz, Izzatdin Abdul, Anh, Bui Ngoc
• Format: Journal Article
• Language: English
• Published: MDPI AG 01.02.2021
• Subjects: combinatory optimization; compromise programming; genetic algorithm; MOP; task assignment; timetabling
• ISSN: 2073-431X; 2073-431X
• DOI: 10.3390/computers10020015

The problem of scheduling is an area that has attracted a lot of attention from researchers for many years. Its goal is to optimize resources in the system. The lecturer’s assigning task is an example of the timetabling problem, a class of scheduling. This study introduces a mathematical model to assign constrained tasks (the time and required skills) to university lecturers. Our model is capable of generating a calendar that maximizes faculty expectations. The formulated problem is in the form of a multi-objective problem that requires the trade-off between two or more conflicting objectives to indicate the optimal solution. We use the compromise programming approach to the multi-objective problem to solve this. We then proposed the new version of the Genetic Algorithm to solve the introduced model. Finally, we tested the model and algorithm with real scheduling data, including 139 sections of 17 subjects to 27 lecturers in 10 timeslots. Finally, a web application supports the decision-maker to visualize and manipulate the obtained results.