An Ant Colony Optimization For Job Scheduling To Minimize Makespan Time

Selvi, V. Agnes Idhaya; Umarani, R.; Saradha, S.

doi:10.47893/ijcct.2015.1266

Cited by 2 publications

(4 citation statements)

References 5 publications

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“…Ant colony algorithm (ACO) is an algorithm for finding optimal paths that are based on the behavior of ants searching for food [15]. Ant behavior when searching for food is the ants initially wander randomly.…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

“…Ant behavior when searching for food is the ants initially wander randomly. When an ant finds food, it walks back to the colony while spreading "markers" (pheromones) that show the path to the food [15]. When the other ants come across the markers, they will follow the path with a certain probability.…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

“…When the other ants come across the markers, they will follow the path with a certain probability. Then they will populate the path with their markers as they bring the food back to the colony [15]. As more ants find the path, it gets stronger until there is a stream of ants traveling to various food sources near the colony [15].…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

“…Then they will populate the path with their markers as they bring the food back to the colony [15]. As more ants find the path, it gets stronger until there is a stream of ants traveling to various food sources near the colony [15]. To use an ant algorithm for scheduling, it is necessary to define the problem in a graph [16].…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

See 3 more Smart Citations

Priority Scheduling Implementation for Exam Schedule

Yanwari¹,

Prabuwono²,

Yudantoro³

et al. 2023

Indonesian J. of Inf. Syst.

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Scheduling is a common problem that has been raised for a long time. Many algorithms have been created for this problem. Some algorithms offer flexibility in terms of constraints and complex operations. Because of that complexity, many algorithms will need huge computation resources and execution time. A platform like a web application has many restrictions such as execution time and computation resources. A complex algorithm is not suited for the web application platform. Priority scheduling is a scheduling algorithm based on a priority queue. Every schedule slot will produce a queue based on the constraints. Each constraint will have a different weight. Weight in queue represents their priority. This algorithm provides a light algorithm that only needs a few computations and execution times. The exam schedule is one of many problems in educational institutions. A web application is a popular platform that can be accessed from everywhere. Many educational institutions use web platforms as their main system platform. Web platforms have some restrictions such as execution time. Due to web platform restrictions, priority scheduling is a suitable algorithm for this platform. In this study, the author tries to implement a priority scheduling algorithm in scheduling cases with a website platform and shows that this algorithm solution can be an alternative for solving scheduling cases with low computational resources.

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Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%