A new genetic algorithm for flexible job-shop scheduling problems

Abstract

Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

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

“…On the other hand, Mastrolilli and Gambardella [55], Gao et al [28], Pezzella et al [66], Amiri et al [3], Yazdani et al [81], Yuan and Xu [83] and Driss et al [20] have better result for the makespan than pbEA.…”

“…[6] 2002 FOSP SA + PDR Schrich et al [71] 2004 FOSP TS + PDR Ho et al [37] 2007 FOSP EA + PDR Liouane et al [52] 2007 FOSP TS + AC Fattahi et al [24] 2007 FOSP TS + SA Pezzella et al [66] 2008 FOSP EA + AL + PDR Moradi et al [57] 2010 FOSP EA + PDR Bozejko et al [10] 2010 FOSP TS + IA Xing et al [80] 2011 FOSP EA + AC Al-Hinai and ElMekkawy [2] 2011 FOSP EA + LS Karimi et al [44] 2012 FOSP VNS Roshanaei et al [70] 2013 FOSP AIS + SA Yuan and Xu [82] 2013 FOSP DEA + LS Wang et al [78] 2013 FOSP EA Farughi et al [23] 2013 FOSP EA + CPM Yuan and Xu [83] 2013 FOSP HSA + LNS Yuan et al [85] 2013 FOSP HSA + LS Mousakhani [60] 2013 FOSP ILS Ziaee [88] 2014 FOSP Meta-Heuristic Driss et al [20] 2015 FOSP EA Within a searching process in random, Moradi et al [57] used a learnable EA to prove FOSP with preventive maintenance activities and the composite dispatching rule to produce population. Tay and Ho [75] used a composite dispatching rule generated for Evolution programming.…”

“…Yuan and Xu [83] also proposed new memetic algorithms for hybridizing EA and local search for the multi-objective PFOSP. Driss et al [20] developed a EA with novel representation for novel and operations research for FOSP reducing the make span. The proposed algorithm is to validate on the series of benchmark data sets and tested on the data received from a drug manufacturing company.…”

A Variable Interval Rescheduling Strategy for Dynamic Flexible Job Shop Scheduling Problem by Improved Genetic Algorithm

“…Hence, it cannot be solved by some exact approaches [5] because of the increased computational time in an exponential manner. In recent years, numerous heuristics approaches are proposed to solve FJSP, and these methods include simulated annealing (SA) [6], tabu search (TS) [7], ant colony optimization (ACO) [8], particle swarm optimization (PSO) [9], artificial bee colony (ABC) [10], GA [11], evolutionary algorithm (EA) [12], and improved or hybrid algorithms [13,14].…”

Dynamic Scheduling of Virtual Cellular Based on Rolling Window under New Tasks

“…From the existing results, the research on the problem of rescheduling at home and abroad mainly focuses on the optimization of the rescheduling method and the evaluation of the performance of the rescheduling [2][3]. The study of rescheduling can be divided into three types: cycle-driven, event-driven and mixed-driven scheduling.…”