Bi-objective optimization research on integrated fixed time interval preventive maintenance and production for scheduling flexible job-shop problem

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.…”

“…Moradi et al [58] developed and compared the four multi-objective optimization methods, which will combine the EA and priority for dispatching rules to reduce the make span and system unavailability, for the integrated FOSP with non-mixed or combined preventive maintenance activities. Xing et al [80] proposed a multipopulation interactive co-genetic algorithm to obtain and increase the performance of evolutionary algorithms of the FOSP.…”

Modified NSGA-II for a Bi-Objective Job Sequencing Problem

“…The methodologies include Linear Programming (Mazdeh et al [19]), dynamic programming (Lewis and Slotnick [20] [24]), Simulated Annealing (SA) Lian [17], hybrid algorithms (Zhang and Wu [25], Tavakkoli-Moghaddam et al [18], Wang et al [26]). Besides, Moradi et al [27] solved bi-objective job sequencing problem by NSGA-II (Non-dominated Sorting Genetic Algorithm-II) [28] and NRGA (Non Ranking Genetic Algorithm) algorithms.…”

An integrated model of production scheduling and maintenance planning under imperfect preventive maintenance

“…The machine's degradation can be described and predicted [26]. But in some cases, a machine may become unavailable because of scheduled maintenance activities or unexpected failures [13]. A good production scheduling makes the company complete more order forms in a certain period.…”