Muhamad Shahbani Abu Bakar

Reactive memory model for ant colony optimization and its application to TSP

Ant colony optimization is one of the most successful examples of swarm intelligent systems. The exploration and exploitation are the main mechanisms in controlling search within the ACO. Reactive search is a framework for automating the exploration and exploitation in stochastic algorithms. Restarting the search with the aid of memorizing the search history is the soul of reaction. It is to increase the exploration only when needed. This paper proposes a reactive memory model to overcome the limitation of the random exploration after restart because of losing the previous history of search. The proposed model is utilized to record the previous search regions to be used as reference for ants after restart. The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model. Based on the results, Max-Min Ant System has been chosen as the base for the modification. The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.

Reactive max-min ant system with recursive local search and its application to TSP and QAP

AbstractAnt colony optimization is a successful metaheuristic for solving combinatorial optimization problems. However, the drawback of premature exploitation arises in ant colony optimization when coupled with local searches, in which the neighborhood’s structures of the search space are not completely traversed. This paper proposes two algorithmic components for solving the premature exploitation, i.e. the reactive heuristics and recursive local search technique. The resulting algorithm is tested on two well-known combinatorial optimization problems arising in the artificial intelligence problems field and compared experimentally to six (6) variants of ACO with local search. Results showed that the enhanced algorithm outperforms the six ACO variants.

RGMDV: An approach to requirements gathering and the management of data virtualization projects

Data virtualization (DV) refers to a set of data stores that enable users to query, access, and manipulate data in a unified, abstracted, and encapsulated manner regardless of data location. Apart from reducing data movement, this system provides a unified, abstracted, real-time, and encapsulated view of information for query purposes. Through its provision of live, virtual data in a timely manner, the DV technique can overcome the obstacles faced by organizations and companies as a result of using other data integration techniques. The systematic planning for the period that precedes DV deployment enables organizations to avoid many challenges related to manageability, usability, data quality, and performance. DV requirements are among the most significant and challenging aspects of a DV project. In this study, an approach has been developed to gather and manage the requirements of a DV design model as an initial step in developing such projects. Expert methods are reviewed to validate and evaluate the p...

Unified strategy for intensification and diversification balance in ACO metaheuristic

This intensification and diversification in Ant Colony Optimization (ACO) is the search strategy to achieve a trade-off between learning a new search experience (exploration) and earning from the previous experience (exploitation). The automation between the two processes is maintained using reactive search. However, existing works in ACO were limited either to the management of pheromone memory or to the adaptation of few parameters. This paper introduces the reactive ant colony optimization (RACO) strategy that sticks to the reactive way of automation using memory, diversity indication, and parameterization. The performance of RACO is evaluated on the travelling salesman and quadratic assignment problems from TSPLIB and QAPLIB, respectively. Results based on a comparison of relative percentage deviation revealed the superiority of RACO over other well-known metaheuristics algorithms. The output of this study can improve the quality of solutions as exemplified by RACO.

Public-private collaboration in spatial data infrastructure: Overview of exposure, acceptance and sharing platform in Malaysia

While Spatial Data Infrastructure (SDI) has been established in Malaysia, the full potential can be further realized. To a large degree, geospatial industry users are hopeful that they can easily get access to the system and start utilizing the data. Some users expect SDI to provide them with readily available data without the necessary steps of requesting the data from the data providers as well as the steps for them to process and to prepare the data for their use. Some further argued that the usability of the system can be improved if appropriate combination between data sharing and focused application is found within the services. In order to address the current challenges and to enhance the effectiveness of the SDI in Malaysia, there is possibility of establishing a collaborative business venture between public and private entities; thus can help addressing the issues and expectations. In this paper, we discussed the possibility of collaboration between these two entities. Interviews with seven entities are held to collect information on the exposure, acceptance and sharing of platform. The outcomes indicate that though the growth of GIS technology and the high level of technology acceptance provides a solid based for utilizing the geospatial data, the absence of concrete policy on data sharing, a quality geospatial data, an authority for coordinator agency, leaves a vacuum for the successful implementation of the SDI initiative.While Spatial Data Infrastructure (SDI) has been established in Malaysia, the full potential can be further realized. To a large degree, geospatial industry users are hopeful that they can easily get access to the system and start utilizing the data. Some users expect SDI to provide them with readily available data without the necessary steps of requesting the data from the data providers as well as the steps for them to process and to prepare the data for their use. Some further argued that the usability of the system can be improved if appropriate combination between data sharing and focused application is found within the services. In order to address the current challenges and to enhance the effectiveness of the SDI in Malaysia, there is possibility of establishing a collaborative business venture between public and private entities; thus can help addressing the issues and expectations. In this paper, we discussed the possibility of collaboration between these two entities. Interviews with seven entit...

Corporate knowledge repository: Adopting academic LMS into corporate environment

The growth of Knowledge Economy has transformed human capital to be the vital asset in business organization of the 21st century. Arguably, due to its white-collar nature, knowledge-based industry is more favorable than traditional manufacturing business. However, over dependency on human capital can also be a major challenge as any workers will inevitably leave the company or retire. This situation will possibly create knowledge gap that may impact business continuity of the enterprise. Knowledge retention in the corporate environment has been of many research interests. Learning Management System (LMS) refers to the system that provides the delivery, assessment and management tools for an organization to handle its knowledge repository. By using the aspirations of a proven LMS implemented in an academic environment, this paper proposes LMS model that can be used to enable peer-to-peer knowledge capture and sharing in the knowledge-based organization. Cloud Enterprise Resource Planning (ERP), referred to...

Improving entrepreneurial opportunity recognition through web content analytics

The ability to recognize and develop an opportunity into a venture defines an entrepreneur. Research in opportunity recognition has been robust and focuses more on explaining the processes involved in opportunity recognition. Factors such as prior knowledge, cognitive and creative capabilities are shown to affect opportunity recognition in entrepreneurs. Prior knowledge in areas such as customer problems, ways to serve the market, and technology has been shows in various studies to be a factor that facilitates entrepreneurs to identify and recognize opportunities. Findings from research also shows that experienced entrepreneurs search and scan for information to discover opportunities. Searching and scanning for information has also been shown to help novice entrepreneurs who lack prior knowledge to narrow this gap and enable them to better identify and recognize opportunities. There is less focus in research on finding empirically proven techniques and methods to develop and enhance opportunity recogniti...

Data warehouse model for monitoring key performance indicators (KPIs) using goal oriented approach

The growth and development of universities, just as other organizations, depend on their abilities to strategically plan and implement development blueprints which are in line with their vision and mission statements. The actualizations of these statements, which are often designed into goals and sub-goals and linked to their respective actors are better measured by defining key performance indicators (KPIs) of the university. The proposes ReGADaK, which is an extended the GRAnD approach highlights the facts, dimensions, attributes, measures and KPIs of the organization. The measures from the goal analysis of this unit serve as the basis of developing the related university’s KPIs. The proposed data warehouse schema is evaluated through expert review, prototyping and usability evaluation. The findings from the evaluation processes suggest that the proposed data warehouse schema is suitable for monitoring the University’s KPIs.