Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid

Harmony search algorithm (HSA) is a population-based metaheuristic optimization algorithm that imitates the music improvisation process where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. Previous studies have shown that HSA has been successfully adapted for solving combinatorial optimization problems such as university course timetabling problem (UCTP). However, HSA encountered a setback in which the convergence rate and accuracy of the obtained results are reduced because of the solutions in the population are eventually about the same during the final iterations. Thus, this thesis proposed hybrid algorithms between HSA and local search based methods (simulated annealing (SA) and/or great deluge (GD)) to enhance the HSA performance for solving curriculum-based course timetabling (CBCTT) problem which is the variant of UCTP. SA is chosen to be hybridize with HSA for solving CBCTT because in literature, SA was successfully hybridize with HSA to solve other domain of problems. GD is chosen to be hybridize with HSA for solving CBCTT because GD has the related procedure with SA

Establishing Effective Workflow Interoperability Framework In The Case Of Domino Workflow And Microsoft Exchange 2000 Server

The availability of a wide range of workflow management system (WFMS) products within the market has allowed users to adopt particular products to meet specific application needs. However, states of the art WFMSs do not have adequate features of interoperability among WFMSs. Failure of interoperability between WFMS products can cause incompatible "islands" of process automation within an organization or between organizations. The research introduces method of realizing workflow interoperability between Domino Workflow from Lotus Corporation and Microsofts Exchange 2000 Server from Microsoft Corporation. Towards the end of this research, the method used has alleviated the strategy, level and model of interoperability between different products that exist between organizations and departments. To realize the workflow interoperability, this research adopted a System Development approach that consists of five stages. The first was to construct a conceptual framework of workflow interoperability between both products. The second was to develop a system architecture. In this stage, the tools of interoperability were analysed. Only two tools were chosen, i.e. Microsoft Exchange Connector for Lotus Notes and Extensible Markup Language (XML) of Document Object Model (DOM) standard. These: tools then were modelled together with Domino Workflow and Microsoft Exchange 2000 Server in the system architecture. The third was to analyse and design the system. In this stage, a specific business process, i.e. leave application was selected to be developed as the prototype. The fourth was to build the prototype to demonstrate the practicality of the method used. Finally, the system was observed and evaluated to validate the effectiveness of the tools used. From the developed prototype, it was concluded that the use of Microsoft Exchange Connector for Lotus Notes and XML of DORA standard realized the workflow interoperability between Domino Workflow and Microsoft Exchange 2000 Server. Two models of workflow interoperability were realised from the developed prototype, i.e. Nested Sub-process model and Parallel Synchronised model. Documents (tasks) from both environments were exchanged by the XML of DOM standard that complied with the Limited Common Application Programming Interface (API) Subset level. The documents were then transferred to each other by the Microsoft Exchange Connector for Lotus Notes that corresponded with the Message Passing strategy

Cervical Cancer Diagnosis System Using Ant-Miner for Managing the Knowledge in Medical Database

The fourth most frequent cause of cancer death in women is cervical cancer. No sign can be observed in the early stages of the disease. In addition, cervical cancer diagnosis methods used in health centers are time-consuming and costly. Data classification has been widely applied in the diagnosis of cervical cancer for knowledge acquisition. However, none of the existing intelligent methods are comprehensible, and they look like a black box to clinicians. In this paper, an ant colony optimization-based classification algorithm, Ant-Miner is applied to analyze the cervical cancer data set. The cervical cancer data set used was obtained from the repository of the University of California, Irvine. The proposed algorithm outperforms the previous approach, support vector machine, in the same domain, in terms of the better result of classification accuracy. The proposed method is implemented as an engine in a prototype system named as the cervical cancer detection system. Evaluation of the prototype system demonstrates a good result on its usability and functionality

Hybrid harmony search with great deluge for UUM CAS curriculum based course timetabling

Producing university course timetabling is a tough and complicated task due to higher number of courses and constraints.The process usually consisted of satisfying a set of hard constraints so as a feasible solution can be obtained.It then continues with the process of optimizing (minimizing) the soft constraints in order to produce a good quality timetable. In this paper, a hybridization of harmony search with a great deluge is proposed to optimize the soft constraints.Harmony search comprised of two main operators such as memory consideration and random consideration operator.The great deluge was applied on the random consideration operator. The proposed approach was also adapted on curriculum-based course timetabling problems of College of Arts and Sciences, Universiti Utara Malaysia (UUM CAS).The result shows that the quality of timetable of UUM CAS produced by the proposed approach is superior than the quality of timetable produced using the current software package

Comparing Document Object Model (DOM) and simple API for XML (SAX) in processing XML document in leave application system

The Extensible Markup Language (XML) consists of two Application Programming Interface (API) i.e. Document Object Model (DOM) and Simple Application of XML (SAX). Previous research has used the DOM API in the Leave Application prototype.In this research, the DOM API based code that developed in the prototype will be changed to SAX API based code.The performance measurement then is carried out to evaluate the used of DOM API and SAX API in the prototype.The evaluation process took place within in each API and also combination of both APIs.From the evaluation process, it was concluded that the use of combination of SAX based code in Domino Workflow environment and DOM based code in Microsoft Exchange 2000 Server produces the lowest processing time that will increase the performance of the leave Application system

Comparing Document Object Model (DOM) and simple API for XML (SAX) in processing XML document in leave application system

The Extensible Markup Language (XML) consists of two Application Programming Inregace (API) i.e. Document Object Model (DOM) and Simple Application of XML(SAX). Previous research hns ued the DOM API in the Leave Application prototype. In this research, the DOM API based code that developed in the prototype will be changed to SAX API based code. The performance measurement then is carried out to evaluate the used of DOM API and SAX API in the prototype. The evaluation process took place within in each API and also combination of both APIs. From the evaluation process,it was concluded that the use of combination of SAX based code in Domino Workflow environment and DOM based code in Microsoft Exchange 2000 Server produces the lowest processing time that will increase the performance of the leave Application system

Construction of Initial Solution Population for Curriculum-Based Course Timetabling using Combination of Graph Heuristics

The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution. This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions. The graph heuristics were set as single and combination of two heuristics. In addition, several ways of assigning courses into room and timeslot are implemented. All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced. The result shows that combination of largest degree followed by saturation degree heuristic produce the highest number of population of initial solutions. The results from this study can be used in the improvement phase of algorithm that uses population of initial solution

Harmony great deluge for solving curriculum based course timetabling problem

University course timetabling which has been determined as non deterministic polynomial problem that accept widely as problem that are intractable.An efficient algorithm does not exist that is guaranteed to find an optimal solution for such problems.The design of good algorithm to find new methods and techniques to solve such problem is a very active area of research.This paper presents the adaption of the hybridizing between harmony search with great deluge algorithm for solving curriculum-based course timetabling problems.The algorithm can be adapted to the problem.Results were not comparatively better than those previously known as best solution.Proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling

A Survey of metaheuristic approaches for curriculum based course timetabling problem

Purpose - The aim of this paper is to explore approaches applied for solving CBCTT by presenting features of implementation related to it.The idea is to prepare references structure for future implementation.There are numerous surveys related to approaches in University course timetabling problem (UCTP) (Babaei, Karimpour, & Hadidi, 2014; Nandhini & Kanmani, 2009).Usually surveys that carried out involved post enrollment course timetabling problem (PECTT) and curriculum-based course timetabling problem (CBCTT) together in one literature. Sometimes the depth of information tend to be reduced as both version need to be highlighted at the same place.This can leads to confusing of references in implementation of new approach in terms of features that each versions support. The review of available approaches in solving CBCTT problem in this paper produces information that can be used for future development and experimentation such as number of instances that should be used, neighborhood structure(s) that can be applied and number of experiment repetitions.As stated by Wolpert & Macready (1997) that there is no unique ‘best’ algorithm which performs better than any other algorithm on every test problem (data instance), hence, this paper provides guidelines for future investigation on solving CBCTT problem using other metaheuristic techniques or approaches

Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem

This paper investigates the construction phase approach in which the sequential order of the courses/lectures applied several combination of graph heuristics to generate a population of initial solutions in curriculum-based course timetabling (CBCTT).The construction of population of initial solution is a prerequisite in a population-based metaheuristic implementation. To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. This process is a crucial task because it can affect the convergence speed and also the quality of the final solution (Rahnamayan, Tizhoosh, & Salama, 2007).This study able to produce a set of initial solution, therefore it is able to contribute to the improvement phase of approach that uses population of initial solutions such as ant colony optimization (ACO) (Socha, Joshua, & Michael, 2002), genetic algorithm (GA) (Lewis & Paechter, 2005), and harmony search algorithm (HSA) (Al-Betar & Khader, 2010).The approach in this study also shows that a feasible timetable can be found for numerous data set problems