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Electimize is a new evolutionary algorithm that simulates the phenomenon of the flow of electrons and electrical conductivity. Previous research proved Electimize to be very efficient in solving NP-hard optimization problems. The algorithm demonstrates higher capabilities in searching the solution space extensively, and identifying global optimal alternatives, if any. The basic advantage of Electimize over other evolutionary algorithms (EAs) lies in the evaluation process of the quality of the solution strings. Unlike other EAs, Electimize evaluates the quality of every value in the solution string independently. Recent research showed that Electimize is slow in converging towards the optimal solution, if the size of problem is increased. This paper presents a new mechanism for enhancing the performance of Electimize by introducing new parameters that would guide the algorithm towards the optimal values. The paper discusses the methodology of the work, the basic theory behind the newly introduced parameters, and the main steps of optimization.