Hybrid discrete particle swarm optimization for multi-objective flexible job-shop scheduling problem

A Novel Memetic Algorithm Based on Decomposition for Multiobjective Flexible Job Shop Scheduling Problem

“…In addition to the successful use of EA, several swarm intelligence algorithms have also been widely used for global search. PSOs were used as global search algorithms in [33][34][35][36]. Besides, shuffled frog leaping [37] and artificial bee colony [38] were integrated with local search in related hybrid algorithms.…”

“…All Pareto solutions marked in bold are listed in Table 6. Next, in Tables 7-10, MOMAD is compared with eight algorithms recently proposed for solving MOFJSP by using Pareto approach that are MOGA [25], PLS [28], HSFLA [37], HMOEA [30], SEA [29], P-EDA [31], hDPSO [34], and PRMOTS + IS [32]. It should be pointed out that these compared algorithms list the results after predefined runs rather than each run in their original literatures.…”

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

“…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.…”

“…Moslehi and Mahnam [59] combined and joined the particle swarm algorithm and a local search algorithm for multi-objective PFOSP with various release times. Shao et al [72] developed a hybrid methodology, which uses the discrete particle swarm optimization for their global search and simulated annealing for local search and for multi-objective PFOSP. Li et al [47] and Li et al [49] proposed a hybridized artificial bee colony algorithm, which is a novel particle swarm methodology, for solving the multi-objective PFOSP.…”

An Efficient Artificial Fish Swarm Model with Estimation of Distribution for Flexible Job Shop Scheduling

“…More recently, with the emergence of new techniques from the field of artificial intelligence, much attention has been devoted to meta-heuristics. The tabu search (TS) has been widely used, such as Brandimart 11 , Mastrolilli and Gambardella 12 , Bozejko et al 13 and Li et al 14 , while the genetic algorithm (GA) has also been examined to be an efficient method such as in Chen et al 15 , Kacem et al 16 , Pezzella et al 17 and Gao et al 18 Besides, some other meta-heuristics have been employed for this problem such as simulated annealing (SA) [19][20][21] , particle swarm optimization (PSO) [22][23][24] , ant colony optimization (ACO) 25 , artificial neural network (ANN) 26 , and artificial immune system (AIS) 27 .…”