[PDF] Top 20 A hybrid genetic-gravitational search algorithm for a multi-objective flow shop scheduling problem Pages 331-348 Download PDF

... appropriate genetic representation ...smaller objective function value) is selected as a parent chromosome to produce different ...bi-objectives problem by using constructive algorithm in ... See full document

... two-machine flow shop under simple linear deterioration. The objective was to obtain a sequence so that the total weighted completion time is ...memetic algorithm by integrating a general ... See full document

... the algorithm converges to the best chromosome, which hopefully represents the optimal solution of the ...this algorithm also depends on the fitness function. A hybrid genetic algorithm ... See full document

... two-stage hybrid flow shop scheduling problem with setup and assembly ...two-stage hybrid flow-shop and then the parts are assembled into products on assembly ... See full document

... a hybrid algorithm called MPSO consisting of particle swarm optimization (PSO), a multiple-type individual enhancement (MIE) scheme based on SA technique, and random-key (RK) encoding scheme for solving the ... See full document

... a flow shop that minimized four combinations of objectives such as makespan, maximum tardiness, total tardiness and flow ...heuristic algorithm for a flow shop with m machines ... See full document

... a hybrid algorithm for the Flexible Job-Shop Scheduling Problem ...This problem involves the optimal use of resources in a flexible production environment in which each operation ... See full document

... ified gravitational emulation local search (MGELS) algorithm to minimize both makespan and total flow ...the flow shop benchmark problem, and the execu- tion of MGELS ... See full document

... new hybrid PSO model named HPSO that combines random-key (RK) encoding scheme, individual enhancement (IE) scheme, and PSO was presented and used to solve the FSSP (Kuo et ...A hybrid alternate two phases ... See full document

... proposed hybrid heuristics for no-wait flow shop scheduling with makespan as objective and found better results than the heuristic of Rajendran ...based genetic algorithm ... See full document

... in flow shop problem where the machines are not continuously ...decoding-based genetic algorithm (SGA) was employed for minimizing makespan for a hybrid flow shop ... See full document

... addressed multi-objective flowshop scheduling ...flowshop problem under two conditions including minimization of makespan and total tardiness penalties and minimization of makespan, total ... See full document

... The problem has been proved to be strongly NP-complete and its total number of possible schedules (sequence) is for ...total flow time and the makespan are of important performance measures, which lead to ... See full document

... the problem – denoted as VSP with Route and Fueling Time Constraints (VSPRFTC) – was presented in which they consider electric ...colony algorithm as a solution ...local search (ILS) algorithm ... See full document

... the genetic algorithm, simulated annealing algorithm, and ant colony optimization algorithm are commonly used for solving energy-saving ...PSO algorithm against PSO and genetic ... See full document

... efficient algorithm which can be easily reconfigured for embedded systems capable of making real-time decisions according to the state of resources and any unplanned or unforeseen ...Harmony search has a ... See full document

... some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on a set of machines such that a specific optimization ... See full document

... the current number of batches. To calculate both NS1 and NS2 the heuristic described in Section 3.3.1 has been employed. Whether the TL size in Table 3 does not yield any integer number, the obtained result must be ... See full document

... a multi-objective NWFP problem where the first objective is the minimization of weighted average of lateness and the other objective is minimization of ... See full document

... the objective of the algorithm is to maximize the fitness ...The problem is tested by several different values and the results are ...in objective values, for using the algorithm in ... See full document