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2 Annals of Computer Science and Information Systems

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InterCriteria Analyzis of Hybrid Ant Colony Optimization Algorithm for Multiple Knapsack Problem

Fidanova Stefka, Ganzha Maria, Roeva Olympia

Annals of Computer Science and Information Systems

2021

Vol. 25

173--180

The local search procedure is a method for hybridization and improvement of the main algorithm, when complex problems are solved. It helps to avoid local optimums and to find faster the global one. In this paper we apply InterCriteria analysis (ICrA) on hybrid Ant Colony Optimization (ACO) algorithm for Multiple Knapsack Problem (MKP). The aim is to study the algorithm behavior comparing with traditional ACO algorithm. Based on the obtained numerical results and on the ICrA approach the efficiency and effectiveness of the proposed local search procedure are confirmed.

Fast BF-ICrA Method for the Evaluation of MO-ACO Algorithm for WSN Layout

Dezert Jean, Fidanova Stefka, Tchamova Albena

Annals of Computer Science and Information Systems

2020

Vol. 21

241--249

In this paper, we present a fast Belief Function based Inter-Criteria Analysis (BF-ICrA) method based on the canonical decomposition of basic belief assignments defined on a dichotomous frame of discernment. This new method is then applied for evaluating the Multiple-Objective Ant Colony Optimization (MO-ACO) algorithm for Wireless Sensor Networks (WSN) deployment.