Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling

Comparative study of pheromone control heuristics in ACO algorithms for solving RCPSP problems

“…This work gravitates on the use of ACO algorithms to the Resource-Constrained Project Scheduling Problem (RCPSP) [33]). The goal of this class of problems is to find an optimal schedule of the activities that compose a project subject to the availability and demand of different resources required to undertake these tasks.…”

Multi-Objective for a Partial Flexible Open Shop Scheduling Problem Using a Priority-Based Evolutionary Algorithm

“…Gao et al [27] combined EA with two neighborhood and friendly structures to develop in a local search to solve the FOSP with non-mixed availability constrains. Gao et al [29] also combined EA with variable neighborhood search to increase in their search ability. Kacem et al [42] developed an assignment and scheduling the procedure, known as approach by localization.…”

“…Rahmati et al [67] developed non-dominated sorting of EA and non dominated ranking EA for multi-objective PFOSP and he proposed new multi-objective Pareto-based modules and a new measure for the multi-objective evaluation. [42] 2002 FOSP EA + AL Baykasoglu et al [7] 2004 FOSP TS + PDR Xia and Wu [79] 2005 FOSP PSO + SA Gao et al [26] 2006 FOSP EA Gao et al [27] 2007 FOSP EA + BSP Zribi et al [89] 2007 FOSP EA + BBA + LS Gao et al [28] 2008 FOSP EA + VNS Tay and Ho [75] 2008 FOSP EA + PDR Wang et al [76] 2008 FOSP FBS + PDR Zhang et al [87] 2009 FOSP PSO + TS Li et al [50] 2010 FOSP EA + VNS Frutos et al [25] 2010 FOSP EA + SA Wang et al [77] 2010 FOSP EA + AIS Gao et al [30] 2010 FOSP EA + AIS Grobler et al [35] 2010 FOSP PSO + PDR Li et al [48] 2010 FOSP TS + VNS Moradi et al [58] 2011 FOSP EA + PDR Moslehi and Mahnam [59] 2011 FOSP PSO + LS Li et al [49] 2011 FOSP PSO Li et al [47] 2011 FOSP PSO Rajkumar et al [68] 2011 FOSP GRASP Chiang and Lin [17] 2013 FOSP EA Rahmati et al [67] 2013 FOSP Gas Shao et al [72] 2013 FOSP PSO + SA Gao et al [29] 2014 FOSP HSA + LS Jia and Hu [41] 2014 FOSP TS Karthikeyan et al [45] 2014 FOSP DFA + LS Li et al [51] 2014 FOSP PSO + TS Rohaninejad et al [69] 2015 FOSP EA Yuan and Xu [84] 2015 FOSP EA + LS Rohaninejad et al [69] proposed a nonlinear IP model and also the hybridized EA with meta-heuristic, which is a multi-attribute decision making method, for multi-objective PFOSP with machines capacity constraints. The computational results are obtained by well-known multi objective algorithms from the literature showed that the proposed algorithm to obtain throughout better performance, especially in the closeness of the solutions result to the Pareto optimal front.…”

MOCANAR: A Multi-Objective Cuckoo Search Algorithm for Numeric Association Rule Discovery

“…Pareto optimality definition says that a solution is a Pareto optimal, if there exists no feasible solution in X_f which would improve some objective without causing a simultaneous deterioration in at least one other objective. [40][41][42][43] studies have used Pareto based approach. Also in this study we use a Pareto based approach that considers four objectives: support, confidence, interestingness and comprehensibility.…”