Evaluation of genetic algorithm and hybrid genetic algorithm-hill climbing with elitist for lecturer university timetabling problem

Abstract

Lecturer university timetabling is an NP-hard real-world problem still needs great attention. The occurrences of the creation of timetable in every university prior to semester starts are compulsory. Its inclusively must cater both hard and soft constraints to satisfy both lecturers and students as the space and time are highly concerned. Genetic Algorithm and Hybrid Genetic Algorithms-Hill Climbing with embedded with elitist mechanism are evaluated with the use of real data sets. The findings have shown Hybrid Genetic Algorithms-Hill Climbing with elitist outperformed Genetic Algorithm with elitist in obtaining an optimal solution. The beauty element offered by Hill Climbing seeking local best individual of the population has given fast convergences with the capability avoiding local optimum. In future, more soft constraints identification of a real problem of lecturer timetabling problem should very much considered as to ensure satisfactions of lecturers and students.