“…WiththeadvantagesofOPDGproblembrought,overthelastdecademanyresearchershave contributed a lot in terms of effort and time to figure out algorithms solve this problem. Many algorithmshavebeenusedfromtheclassictoartificialintelligenceandevolutionsuchasanalytical method (Wang&Nehrir,2004;Acharya,Mahat,&Mithulananthan,2006;Hamedi&Gandomkar, 2012;Gozel&Hocaoglu,2009),lagrangemultiplier(LM) (Gautam&Mithulananthan,2007),interior point method (IPM) (Khoa, Binh, & Tran, 2006), teaching-learning based optimization (TLBO) (Garcíal&Mena,2013),tabusearch(TS) (Naraetal.,2001),geneticalgorithm(GA) (Borges& Falcao,2006;Pisică,Bulac,&Eremia,2009;Kalantari&Kazemi,2011),differentialevolution(DE) (Arya,Choube,&Arya,2011),antcolonyoptimization(ACO) (Falaghi&Haghifam,2007),particle swarm optimization (PSO) (El-Zonkoly, 2011;Reddy, Dey, & Paul, 2012), bacterial foraging optimizationalgorithm(BFOA) (MohamedImran&Kowsalya,2014),flowerpollinationalgorithm (FPA) (Reddy,Reddy,&Manohar,2016),greywolfoptimizer(GWO) (Sultanaetal.,2016),cuckoo search(CS) (Moravej&Akhlaghi,2013),gravitationalsearchalgorithm(GSA) (Mistry,Bhavsar,& Roy,2012),batalgorithm(BA) (Behera,Dash,&Panigrahi,2015),andharmonysearchalgorithm (HSA) (Kollu, Rayapudi, & Sadhu, 2012), etc. Besides, many researchers have hybridized two optimizationalgorithmstoobtainabettersolution.AnewhybridmethodofGAandTSisintroduced by (Gandomkar,Vakilian,&Ehsan,2005),while (Cellietal.,2005)implementedaapproachbased onaGAandan ε -constrainedmethod.…”