A Micro-Genetic Algorithm Approach for Soft Constraint Satisfaction Problem in University Course Scheduling

A university course timetabling problem is a combination of optimization problems. The problems are more challenging when a set of events need to be scheduled in the time slot, to be located to the suitable rooms, which is subjected to several sets of hard and soft constraints. All these constraints that exist as regulations within each resource for the event need to be fulfilled in order to achieve the optimum tasks. In addition, the design of course timetables for universities is a very difficult task because it is a non-deterministic polynomial, (NP) hard problem. This problem can be minimized by using a Micro Genetic Algorithm approach. This approach, encodes a chromosome representation as one of the key elements to ensure the infeasible individual chromosome produced is minimized. Thus, this study proposes an encoding chromosome representation using one-dimensional arrays to improve the Micro Genetic algorithm approach to soft constraint problems in the university course schedule. The research contribution of this study is in developing effective and feasible timetabling software using Micro Genetic Algorithm approach in order to minimize the production of an infeasible individual chromosome compared to the existing optimization algorithm for university course timetabling where UNITAR International University have been used as a data sample. The Micro Genetic Algorithm proposed has been tested in a test comparison with the Standard Genetic algorithm and the Guided Search Genetic algorithm as a benchmark. The results showed that the proposed algorithm is able to generate a minimum number of an infeasible individual chromosome. The result from the experiment also demonstrated that the Micro Genetic Algorithm is capable to produce the best course schedule to the UNITAR International University

Human Resource Management Practices and Organisational Performance : A Study on Administrators in Universiti Teknologi MARA

This quantitative research aims to determine the relationship between human resource management practices and performance management in Universiti Teknologi MARA. The study is conducted to the administrators who involve in the human resource matters and administration in all faculty, branch campus and department. Instrument of assessment questionnaire by Chand and Katou (2007) and Brewster and Hegewisch (1994) used to measure human resource management practices and instrument questionnaire by de Waal and Frijns (2011) to measure organisational performance. All variables in HRM practices have relationship with the organisational performance, where manpower planning and quality circle have the strongest relationship. Of the six hypotheses tested, five were substantiated and one was not. It is also indicated that quality circle has the most correlation effect on organisational performance

Using Distributed Agents to Create University Course Timetables Addressing Essential & Desirable Constraints and Fair Allocation of Resources

In this study, the University Course Timetabling Problem (UCTP) has been investigated. This is a form of Constraint Satisfaction Problem (CSP) and belongs to the NP-complete class. The nature of a such problem is highly descriptive, a solution therefore involves combining many aspects of the problem. Although various timetabling algorithms have been continuously developed for nearly half a century, a gap still exists between the theoretical and practical aspects of university timetabling. This research is aimed to narrow the gap. We created an agent-based model for solving the university course timetabling problem, where this model not only considers a set of essential constraints upon the teaching activities, but also a set of desirable constraints that correspond to real-world needs. The model also seeks to provide fair allocation of resources. The capabilities of agents are harnessed for the activities of decision making, collaboration, coordination and negotiation by embedding them within the protocol designs. The resulting set of university course timetables involve the participation of every element in the system, with each agent taking responsibility for organising of its own course timetable, cooperating together to resolve problems. There are two types of agents in the model; these are Year-Programme Agent and Rooms Agent. In this study, we have used four different principles for organising the interaction between the agents: First-In-First-Out & Sequential (FIFOSeq), First-In-First-Out & Interleaved (FIFOInt), Round-Robin & Sequential (RRSeq) and Round-Robin & Interleaved (RRInt). The problem formulation and data instances of the third track of the Second International Timetabling Competition (ITC-2007) have been used as benchmarks for validating these implemented timetables. The validated results not only compare the four principles with each other; but also compare them with other timetabling techniques used for ITC-2007. The four different principles were able to successfully schedule all lectures in different periods, with no instances of two lectures occupying the same room at the same time. The lectures belonging to the same curriculum or taught by the same teacher do not conflict. Every lecture has been assigned a teacher before scheduling. The capacity of every assigned room is greater than, or equal to, the number of students in that course. The lectures of each course have been spread across the minimum number of working days with more than 98 percent success, and for more than 75 percent of the lectures under the same curriculum, it has been possible to avoid isolated deliveries. We conclude that the RRInt principle gives the most consistent likelihood of ensuring that each YPA in the system gets the best and fairest chance to obtain its resources

Case-based reasoning for course timetabling problems

The research in this thesis investigates Case-Based Reasoning (CBR), a Knowledge-Based Reasoning technique that proved to be capable of providing good solutions in educational course timetabling problems. Following the basic idea behind CBR, experiences in solving previous similar timetabling problems are employed to find the solutions for new problems. A basic CBR system that is hierarchically organized with structured knowledge representations by attribute graphs is proposed in Chapter Four. The system is then further improved to solve a wider range of problems, which is described in Chapter Five. Evaluations on a large number of experiments indicate that this approach could provide a significant step forward in timetabling and scheduling research. This basic system works well on relatively small problems. To deal with this drawback a multiple-retrieval approach that partitions large timetabling problems into small solvable sub-problems is presented in Chapter Six. Good results are obtained from a wide range of experiments. In Chapter Seven, a new idea is introduced in CBR for solving timetabling problems by investigating the approach to select the most appropriate heuristic method rather than to employ it directly on the problem, in the attempt to raise the level of generality at which we can operate. All the evidence obtained from the first stage experiments indicates that there is a range of promising future directions. Finally in Chapter Eight the results of the work are evaluated and some directions for future work are present

Case-based reasoning for course timetabling problems

The research in this thesis investigates Case-Based Reasoning (CBR), a Knowledge-Based Reasoning technique that proved to be capable of providing good solutions in educational course timetabling problems. Following the basic idea behind CBR, experiences in solving previous similar timetabling problems are employed to find the solutions for new problems. A basic CBR system that is hierarchically organized with structured knowledge representations by attribute graphs is proposed in Chapter Four. The system is then further improved to solve a wider range of problems, which is described in Chapter Five. Evaluations on a large number of experiments indicate that this approach could provide a significant step forward in timetabling and scheduling research. This basic system works well on relatively small problems. To deal with this drawback a multiple-retrieval approach that partitions large timetabling problems into small solvable sub-problems is presented in Chapter Six. Good results are obtained from a wide range of experiments. In Chapter Seven, a new idea is introduced in CBR for solving timetabling problems by investigating the approach to select the most appropriate heuristic method rather than to employ it directly on the problem, in the attempt to raise the level of generality at which we can operate. All the evidence obtained from the first stage experiments indicates that there is a range of promising future directions. Finally in Chapter Eight the results of the work are evaluated and some directions for future work are present