We consider flowshop environments that consist of multiple stages and multiple machines in each stage. The flowshops are flexible in the sense that a task within a stage can be processed by any of the machines in the stage. We refer to this design as the hybrid flowshop. Our objective is to schedule a set of n jobs so as to minimize makespan. The problem is NP-complete even in the case of a sin...

This research presents a novel approach to solve m-machine no-wait flowshop scheduling problem. A continuous flowshop problem with total flowtime as criterion is considered applying a hybrid evolutionary algorithm. The performance of the proposed method is evaluated and the results are compared with the best known in the literature. Experimental tests show the superiority of the evolutionary hy...

In this paper, we propose different local search algorithms to solve a realistic variant of the flowshop problem. The variant considered here is a hybrid flexible flowshop problem with sequence-dependent setup times, and with the objective of minimizing the total tardiness. In this variant of flowshop, stage skipping might occur, i.e., not all stages must be visited by all jobs. This scheduling...

The paper describes an algorithm for solving the scheduling problem of a hybrid flowshop (flowshop with multiple processors, FSMP). The algorithm is a combination of genetic algorithm and tabu search, and the batch processes it is applied on are modeled by a model of time requirements. The paper describes the algorithm and compares its performance with other optimization techniques.

The two-stage assembly flowshop scheduling problem is addressed with the objective of minimizing total tardiness. An insertion algorithm, a genetic algorithm, and a hybrid of the insertion and genetic algorithms, are developed for the problem. Conducted computational experiments reveal that the hybrid algorithm significantly outperforms the genetic algorithm while the best performing algorithm ...

this article addresses a multi-stage flowshop scheduling problem with equal number of unrelated parallel machines. the objective is to minimize the makespan for a given set of jobs in the system. this problem class is np-hard in the strong sense, so a hybrid heuristic method for sequencing and then allocating operations of jobs to machines is developed. a number of test problems are randomly ge...

The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society ...

This paper deals with a realistic variant of flowshop scheduling, namely the hybrid flexible flowshop. A hybrid flowshop mixes the characteristics of regular flowshops and parallel machine problems by considering stages with parallel machines instead of having one single machine per stage. We also investigate the flexible version where stage skipping might occur, i.e., not all stages must be vi...

A hybrid Taguchi-based genetic algorithm (HTGA) is developed for solving multi-objective flowshop scheduling problems (FSPs). Search performance is improved by using Taguchi-based crossover to avoid scheduling conflicts, and dynamic weights are randomly selected by a fuzzy inference system. The conventional approach to selecting dynamic weights randomly ignores small value for the objective whe...