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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics International Journal of Supply Chain Management
Yuhanis Yusof
Universiti Utara Malaysia
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Integrated bio-search approaches with multi-objective algorithms for optimization and classification problem Mohammad Aizat Basir; Mohamed Saifullah Hussin; Yuhanis Yusof
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.15141

Abstract

Optimal selection of features is very difficult and crucial to achieve, particularly for the task of classification. It is due to the traditional method of selecting features that function independently and generated the collection of irrelevant features, which therefore affects the quality of the accuracy of the classification. The goal of this paper is to leverage the potential of bio-inspired search algorithms, together with wrapper, in optimizing multi-objective algorithms, namely ENORA and NSGA-II to generate an optimal set of features. The main steps are to idealize the combination of ENORA and NSGA-II with suitable bio-search algorithms where multiple subset generation has been implemented. The next step is to validate the optimum feature set by conducting a subset evaluation. Eight (8) comparison datasets of various sizes have been deliberately selected to be checked. Results shown that the ideal combination of multi-objective algorithms, namely ENORA and NSGA-II, with the selected bio-inspired search algorithm is promising to achieve a better optimal solution (i.e. a best features with higher classification accuracy) for the selected datasets. This discovery implies that the ability of bio-inspired wrapper/filtered system algorithms will boost the efficiency of ENORA and NSGA-II for the task of selecting and classifying features.
Increasing data storage of coloured QR code using compress, multiplexing and multilayered technique Azizi Abas; Yuhanis Yusof; Roshidi Din; Fazli Azali; Baharudin Osman
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2481

Abstract

Quick response (QR) code is a printed code of black and white squares that is able to store data without the use of any of the electronic devices. There are many existing researches on coloured QR code to increase the storage capacity but from time to time the storage capacity still need to be improved. This paper proposes the use ofcompress, multiplexing and multilayered techniques, as an integrated technique known as CoMM, to increase the storage of the existing QR code. The American Standard Code for Information Interchange (ASCII) text characters are used as an input and performance is measured by the number of characters that can be stored in a single black and white QR code version 40. The experiment metrics also include percentage of missing characters, number of produced QR code, and elapsed time to create the QR code. Simulation results indicate that the proposed algorithm stores 24 times more characters than the black and white QR code and 9 times more than other coloured QR code. Hence, this shows that the coloured QR code has the potential of becoming useful mini-data storage as it does not rely on internet connection.
Determining Multi-Criteria Supplier Selection towards Sustainable Development of IT Project Outsourcing Fauziah Baharom; Prashaya Fusiripong; Yuhanis Yusof
International Journal of Supply Chain Management Vol 6, No 3 (2017): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.161 KB)

Abstract

Due to competitiveness in the global business, many organizations have sought alternative to improve their businesses and operations by outsourcing projects and this includes Information Technology (IT) projects. Selecting the most suitable IT supplier is important to ensure sustainable development of the projects. Supplier is selected based on a set of criteria used in the decision process. The criteria can be comprised into tangible and intangible criteria. Many studies have attempted to determine the criteria to be used in selecting IT supplier, nevertheless, it has yet to be reported on a standardize set of criteria to be used in IT outsourcing projects. Thus outsourcing decisions are often made under uncertainty and incomplete information which leads to weak decision and high risk of projects failure. Therefore, the study aimed to determine multi-criteria for supplier selection in order to ensure the sustainable development of IT outsourcing projects. The criteria were identified using comprehensive review approach that utilizes searching information related to multi criteria supplier selection in IT outsourcing and successful criteria of IT outsourcing projects. As a result, the identified criteria is proposed as a standardize criteria in selecting supplier for IT outsourcing projects. Such a contribution is hoped to benefit businesses for various IT outsourcing projects.
An improved artificial bee colony with perturbation operators in scout bees’ phase for solving vehicle routing problem with time windows Salah Mortada; Yuhanis Yusof
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i2.pp656-666

Abstract

An example of a combinatorial problem is the vehicle routing problem with time windows (VRPTW), which focuses on choosing routes for a limited number of vehicles to serve a group of customers in a restricted period. Meta-heuristics algorithms are successful techniques for VRPTW, and in this study, existing modified artificial bee colony (MABC) algorithm is revised to provide an improved solution. One of the drawbacks of the MABC algorithm is its inability to execute wide exploration. A new solution that is produced randomly and being swapped with best solution when the previous solution can no longer be improved is prone to be trapped in local optima. Hence, this study proposes a perturbed MABC known as pertubated (P-MABC) that addresses the problem of local optima. P-MABC deploys five types of perturbation operators where it improvises abandoned solutions by changing customers in the solution. Experimental results show that the proposed P-MABC algorithm requires fewer number of vehicles and least amount of travelled distance compared with MABC. The P-MABC algorithm can be used to improve the search process of other population algorithms and can be applied in solving VRPTW in domain applications such as food distribution.
Co-Authors Azizi Abas Baharudin Osman Fauziah Baharom Fazli Azali Mohamed Saifullah Hussin Mohammad Aizat Basir Prashaya Fusiripong Roshidi Din Salah Mortada