A flow shop scheduling problem involves scheduling jobs on multiple machines in series in order to optimize a given criterion. The flow time of a job is the amount of time the job spent before its completion and the stretch of the job is the ratio of its flow time to its processing time. In this paper, a hybrid genetic algorithm (HGA) approach is proposed for minimizing the total stretch in flo...

Two scheduling methods based on Extreme Value Theory (SEVAT) and Genetic Algorithms (GA) are developed. The SEVAT approach is a schedule building approach that creates a statistical profile of schedules through random sampling and predicts the potential' of a schedule alternative. The GA approach, on the other hand, is a schedule permutation approach, in which a population of schedules are init...

In a distributed system or communication network tasks may need to be executed on more than one processor. For time-critical tasks, the timing constraints are typically given as end-to-end release-times and deadlines. This paper describes algorithms to schedule a class of systems where all the tasks execute on different processors in turn in the same order. This end-to-end scheduling problem is...

In this work, multicriteria decision making objective for flow shop scheduling with sequence dependent set up time and due dates have been developed. Multicriteria decision making objective includes total tardiness, total earliness and makespan simultaneously which is very effective decision making for scheduling jobs in modern manufacturing environment. As problem of flow shop scheduling is NP...

The job shop problem is an important part of scheduling in the manufacturing industry. A new intelligent algorithm named Shuffled Complex Evolution (SCE) algorithm is proposed in this paper with the aim of getting the minimized makespan. The sequence mapping mechanism is used to change the variables in the continuous domain to discrete variables in the combinational optimization problem; the se...

Variable neighborhood search (VNS) systematically exploits the idea to alternate between neighborhoods within a local search [4]. Several VNS variants have been described so far and many of them have been applied with success to a variety of combinatorial optimization problems; see [3, 4] for an overview. Yet, even though scheduling is a central problem in production environments, we are not aw...

tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. hence, integration has been proposed to decide about these problems concurrently. main problem in integration is how we can relate pro...

Fine-grained accelerators have the potential to deliver significant benefits in various platforms for embedded signal processing. Due to the moderate complexity of their targeted operations, these accelerators must be managed with minimal run-time overhead. In this paper, we present a methodology for applying flow-shop scheduling techniques to make effective, lowoverhead use of fine-grained DSP...