Enhanced Imperialist Competitive Algorithm for the Cell Formation Problem Using Sequence Data

Imperialist Competitive Algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population-based algorithm which has achieved a great performance in comparison to other metaheuristics. This study is about developing enhanced ICA approach to solve the Cell Formation Problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Influence of Various Factors on Stability of CoSPc in LPG Sweetening Process

IFP Group Technology “Sulfrex process" was used in Iran-s South Pars Gas Complex Refineries for removing sulfur compounds such as mercaptans, carbonyl sulfide and hydrogen sulfide, which uses sulfonated cobalt phthalocyanine dispersed in alkaline solution as catalyst. In this technology, catalyst and alkaline solution were used circularly. However the stability of catalyst due to effect of some parameters would reduce with the running of the unit and therefore sweetening efficiency would be decreased. Hence, the aim of this research is study the factors effecting on the stability of catalyst.