Penerapan Algoritma ACO untuk Penjadwalan Kuliah Pengganti pada Perguruan Tinggi (Studi Kasus: Program Studi Informatika, Universitas Multimedia Nusantara)

2019 ◽  
Vol 9 (2) ◽  
pp. 79-85
Author(s):  
Indah Noviasari ◽  
Andre Rusli ◽  
Seng Hansun
Keyword(s):  
Ant Colony Optimization ◽  
Educational Institution ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Ant Colony ◽  
Scheduling Problems ◽  
Perceived Ease Of Use ◽  
Ant Colony Optimization Algorithm ◽  
Scheduling System ◽  
Course Scheduling

Students and scheduling are both essential parts in a higher educational institution. However, after schedules are arranged and students has agreed to them, there are some occasions that can occur beyond the control of the university or lecturer which require the courses to be cancelled and arranged for replacement course schedules. At Universitas Multimedia Nusantara, an agreement between lecturers and students manually every time to establish a replacement course. The agreement consists of a replacement date and time that will be registered to the division of BAAK UMN which then enter the new schedule to the system. In this study, Ant Colony Optimization algorithm is implemented for scheduling replacement courses to make it easier and less time consuming. The Ant Colony Optimization (ACO) algorithm is chosen because it is proven to be effective when implemented to many scheduling problems. Result shows that ACO could enhance the scheduling system in Universitas Multimedia Nusantara, which specifically tested on the Department of Informatics replacement course scheduling system. Furthermore, the newly built system has also been tested by several lecturers of Informatics UMN with a good level of perceived usefulness and perceived ease of use. Keywords—scheduling system, replacement course, Universitas Multimedia Nusantara, Ant Colony Optimization

scholarly journals Comparison Performance of Genetic Algorithm and Ant Colony Optimization in Course Scheduling Optimizing

2016 ◽  
Vol 3 (2) ◽  
pp. 149-158 ◽  
Author(s):  
Imam Ahmad Ashari ◽  
Much Aziz Muslim ◽  
Alamsyah Alamsyah
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Optimal Solution ◽  
Optimization Techniques ◽  
Ant Colony ◽  
Scheduling Problems ◽  
Ant Colony Optimization Algorithm ◽  
Course Scheduling ◽  
The University

Scheduling problems at the university is a complex type of scheduling problems. The scheduling process should be carried out at every turn of the semester's. The core of the problem of scheduling courses at the university is that the number of components that need to be considered in making the schedule, some of the components was made up of students, lecturers, time and a room with due regard to the limits and certain conditions so that no collision in the schedule such as mashed room, mashed lecturer and others. To resolve a scheduling problem most appropriate technique used is the technique of optimization. Optimization techniques can give the best results desired. Metaheuristic algorithm is an algorithm that has a lot of ways to solve the problems to the very limit the optimal solution. In this paper, we use a genetic algorithm and ant colony optimization algorithm is an algorithm metaheuristic to solve the problem of course scheduling. The two algorithm will be tested and compared to get performance is the best. The algorithm was tested using data schedule courses of the university in Semarang. From the experimental results we conclude that the genetic algorithm has better performance than the ant colony optimization algorithm in solving the case of course scheduling.

Job Shop-Scheduling Problems- Single Process

2010 ◽  
Vol 44-47 ◽  
pp. 330-334
Author(s):  
Ramezan Ali Mahdavinejad
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Ant Colony ◽  
Dispatching Rules ◽  
Scheduling Problems ◽  
Ant Colony Optimization Algorithm ◽  
Jobshop Scheduling ◽  
Single Process

In this paper, single-processors jobshop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. The process of finding the best solution will be improved by using the suitable hybrid of priority dispatching rules. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. By solving some problems as samples (i.e. Fisher's & Thomson's problems), this algorithm is compared with the others. The results show that when the size of the problem becomes lorger, the deviation from lower limit increases, but its rate decreases with the size of the problems, so that it reaches to its limit.

scholarly journals The Development of Autonomous Examination Paper Application: A Case Study in UiTM Cawangan Perlis

2019 ◽  
Vol 4 (2) ◽  
pp. 21-30
Author(s):  
Noorfaizalfarid Mohd Noor ◽  
Nadhirah Mohd Napi ◽  
Izzati Farzana Ibni Amin
Keyword(s):  
Ad Hoc ◽  
Educational Institution ◽  
Vital Role ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
University Evaluation ◽  
The University ◽  
Examination Paper

Examination is a vital role to measure the capabilities of students in their learning. Hence, generating question paper in an effective way is a decisive job for educators in educational institution. Using traditional method, it is monotonous and time consuming. Today, Autonomous Examination Paper (AEP) is used to produce exam paper. Many researchers have proposed effective AEPs to be used by educators. This paper aims to investigate about AEP development and to construct AEP in UiTM Cawangan Perlis. As a result, Ad-Hoc Question Paper Application (AQPA) has been developed using Fisher-Yates algorithm to generate questions for exam paper in the university. Evaluation based on Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) reveal that lecturers in the university manage to interact with AQPA and willing to use it as a tool to minimize their workload. However, more improvement must be done on AQPA to be an effective AEP. To conclude, AEP brings significance to educators and can be improved with the latest technology.

scholarly journals Simultaneous Scheduling of Machines and AGVs in FMS Through Ant Colony Optimization Algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 1392-1397
Keyword(s):  
Ant Colony Optimization ◽  
Manufacturing Systems ◽  
Material Handling ◽  
Manufacturing System ◽  
Response Times ◽  
Life Cycles ◽  
Ant Colony ◽  
Scheduling Problems ◽  
Ant Colony Optimization Algorithm ◽  
Simultaneous Scheduling

High amount of flexibility and quick response times have become essential features of modern manufacturing systems where customers are demanding a variety of products with reduced product life cycles. Flexible manufacturing system (FMS) is the right choice to achieve these challenging tasks. The performance of FMS is dependent on the selection of scheduling policy of the manufacturing system. In Traditional scheduling problems machines are as considered alone. But material handling equipment’s are also valuable resources in FMS. The scheduling of AGVs is needed to be optimized and harmonized with machine operations. Scheduling in FMS is a well-known NP-hard problem due to considerations of material handling and machine scheduling. Many researchers addressed machine and AGVs individually. In this work an attempt is made to schedule both the machines and AGVs simultaneously. For solving these problems-a new metaheuristic Ant Colony Optimization (ACO) algorithm is proposed.

Sustaining Job Performance through Technology Acceptance with Usage of Whatsapp Mobile Application

2020 ◽  
Vol 5 (1) ◽  
pp. 123
Author(s):  
Nor Hayati Kassim ◽  
Norlina Mohamed Noor ◽  
Jati Kasuma ◽  
Juliza Saleh ◽  
Ceaser Dealwis ◽  
...  
Keyword(s):  
Job Performance ◽  
Technology Acceptance ◽  
Mobile Applications ◽  
Mobile Application ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Maximum Efficiency ◽  
Perceived Ease Of Use ◽  
Positive Attitudes ◽  
Willingness To Use

Companies are now recognizing that their employees require a spectrum of mobile applications in order to achieve maximum efficiency at the workplace. Mobile applications such as WeChat, Twitter and WhatsApp via smartphones have become influential tools and extensively used by employees at the workplace. This state-of-the-art technology in communication has penetrated various fields, including routine administrative jobs at the workplace. The objective of this research is toinvestigate the acceptance of the WhatsApp mobile application for formal use among support staff at The Commission of the City of Kuching North, Sarawak (DBKU). Perceived usefulness, perceived ease of use and behavioral intention of the users in using WhatsApp are the variables measured for job performance. The researchers utilized convenience sampling, whereby a total of 105 employees from two departments participated in the investigation. Data was collected using a set of selfadministered questionnaires which was adapted from Davis. The findings revealed that perceived usefulness and perceived ease of use of WhatsApp as a means of communication were significant for job performance at DBKU. The employees felt more competent during their formal interaction at the workplace as less effort was needed while using WhatsApp. The existence of features which were user-friendly and easy operational functions helped to create positive attitudes when utilizing the application. Faster feedback, ease of use, and convenience were some of the reasons for the employees’ willingness to use WhatsApp for communication at the workplace.

Modeling and optimizing logistics, information, economic and financial intercluster cooperation using the ant colony optimization algorithm

2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Population Decline ◽  
Innovation System ◽  
Federal District ◽  
Original Model ◽  
Ant Colony ◽  
Industrial Agglomeration ◽  
Ant Colony Optimization Algorithm

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.

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