This week you start your first step toward building your research proposal proje

Question

This week you start your first step toward building your research proposal project in Project assignment 2 in which you identify your selected research problem. Use this application assignment to achieve two goals: Learn how to search an online data base. Identify and review two journal articles in that data base that are related to your selected research problem. All VIU students have a free access to the online JSTOR database and other data bases. Search JSTOR or Other data bases, depending on your selected topic of research, for one journal article that is related to your selected research problem, download the article (not the abstract) and review it and keep it, you will have to include it in your submission for this application. Identify the Research Problem discussed in your downloaded article. Explain the problem in your own words, and discuss the importance of the study. Identify Hypotheses. Identify whether or not research hypotheses are present in such study.

Explanation / Answer

Paper Studied: Dorigo, M., Birattari, M., & Stutzle, T. (2006). Ant colony optimization. IEEE computational intelligence magazine

Gist got from the paper:

ACO is a population-based high-level procedure that provides the inexact result to difficult optimization problems [21]. While using Ant Colony Optimization, a group of software agent known as ARTIFICIAL ANTS is assigned with a task to find a favorable solution to the given problem of optimization. The problem must be transmuted into a new problem of discovering the best path on a weighted graph. The ants incrementally construct the solution by operating on the graph. The process of solution construction is stochastic and is influenced by a pheromone model which means a set of graph components whose values altered at the runtime by the ants [21]. ACO algorithm is constructed on indirect communication within the colony, full of artificial ants and mediated by the pheromone trail. The pheromone trail in Ant Colony Optimization acts as a numerically distributed statistics which are used by ants to create a possible solution to the problem and is also adapted by the ants to exhibit their search experience [21].

Second paper Studied:  Karaboga, D. (2010). Artificial bee colony algorithm. scholarpedia

Gist of paper 2: Karaboga introduced ABC algorithm in 2005. It is a swarm-based, population-based algorithm, inspired by the intelligent foraging behaviour of honey bees and is based on the model proposed by Tereshko and Loengarov. ABC algorithm consists of three elemental components: employed foraging bees, unemployed foraging bees and food source [22]. The first two components, employed and unemployed bees search for rich food sources close to the hive. To implement ABC, the given problem is first converted to the problem of finding the best parameter vector which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solution vectors and then iteratively improve them by employing the strategies: moving towards better solutions by means of a neighbour search mechanism while abandoning poor solutions [22].

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