The unrelated parallel machine scheduling problem, in its most general form, is applicable to many manufacturing and service environments. This problem requires the scheduling of a group of independent jobs on unrelated parallel machines as well as the sequencing of the jobs on each individual machine. In this paper, we propose a genetic algorithm with adaptive crossover selection to schedule ...

Parallel machine scheduling, also known as parallel task scheduling, involves the assignment of multiple tasks onto the system architecture’s processing components (a bank of machines in parallel). A basic model involving m machines and n independent jobs is the foundation of more complex models. Here, the jobs are allocated according to resource availability following some allocation rule. The...

For a scheduling problem on parallel machines, the power of preemption is defined as the ratio of the makespan of an optimal non-preemptive schedule over the makespan of an optimal preemptive schedule. For m uniform parallel machines, we give the necessary and sufficient conditions under which the global bound of 2 − 1/m is tight. If the makespan of the optimal preemptive schedule is defined by...

Triggered by the ever increasing advancements in processor and networking technology, a cluster of workstations and/or PCs connected by a high-speed network has become a viable and cost-effective platform for the execution of computation intensive parallel applications. However, realizing the goal of efficient cluster computing entails handling a number of resource management chores. In particu...

This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the mo...

We study scheduling problems with controllable processing times on parallel machines, in which the decision-maker selects an actual processing time for each job from a given interval. The chosen values of the processing times must be such that each job can be preemptively scheduled within a given time interval, and it is required to minimize a certain cost function that depends on the chosen ti...

Scheduling is an important subject of production and operations management area. In flow-shop scheduling, the objective is to obtain a sequence of jobs which when processed in a fixed order of machines, will optimize some well defined criteria. The concept of transportation time is very important in scheduling. Transportation can be done by robots. In situations that robots are used to transpor...

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...

Heterogeneous distributed computing is the tuned use of a network of machines of diverse architectures and computational power, by directing individual portions of a parallel program to the machine(s) best suited for their execution. Load balancing algorithms for an HCE attempt to improve the response times for parallel programs by adapting the process scheduling policies on individual machines...