cloud computing is the latest technology that involves distributed computation over the internet. it meets the needs of users through sharing resources and using virtual technology. the workflow user applications refer to a set of tasks to be processed within the cloud environment. scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of su...

We study stochastic combinatorial optimization problems where the objective is to minimize expected maximum load (a.k.a. makespan). In this framework, we have a set of n tasks and m resources, each task j uses some subset resources. Tasks random sizes $$X_j$$ , our goal non-adaptively select t over all on any resource i total size selected that use i. For example, when resources are points inte...

We study methods for the exact solution of unrelated parallel machine problem with makespan minimization, generally denoted as R||C max . Our original application arises from automotive assembly process where tasks needs to be distributed among several robots. This involves solutions instances, which proved hard a MILP solver since objective induces weak LP relaxation bounds. To improve these b...

We consider the problem of scheduling on parallel uniformly related machines, where preemptions are allowed and the machines are controlled by selfish agents. Our goal is to minimize the makespan, whereas the goal of the agents is to maximize their profit. We show that a known algorithm is monotone and can therefore be used to create a truthful mechanism for this problem which achieves the opti...

In the graph balancing problem the goal is to orient a weighted undirected graph to minimize the maximum weighted in-degree. This special case of makespan minimization is NP-hard to approximate to a factor better than 3/2 even when there are only two types of edge weights. In this note we describe a simple 3/2 approximation for the graph balancing problem with two-edge types, settling this very...

A two-stage algorithm for scheduling preemptive jobs on parallel machines with minimum makespan criterion and requirements for limited renewable resources and existence of sequence dependent setup times is investigated. In the first stage of the algorithm a set of best elementary feasible plans is obtained through column generation. For the second stage we compare genetic algorithms for sequenc...

This paper considers our work in progress on the problem of scheduling production activities in a real-life manufacturing plant. The problem is modelled as a two-stage flexible flow shop problem with minimization of the makespan and the number of tardy jobs. The design approach of an evolutionary algorithm is described. Preliminary experiments are performed and results obtained show the improve...

This paper deals with a single machine scheduling problem with availability constraints. The jobs are splitable and lower bound on the size of each sub-job is imposed. The objective is to find a feasible schedule that minimizes the makespan. The proposed scheduling problem is proved to be NP-hard in the strong sense. Some effective heuristic algorithms are then proposed. Additionally, computati...

Workflow applications in science and engineering have steadily increased in variety and scale. Coinciding with this increase has been the relentless effort to improve the performance of these applications through exploiting the abundance of resources in hyper-scale clouds and with little attention to resources efficiency. The inefficient use of resources when executing scientific workflows resu...

Task scheduling is an essential aspect of parallel processing system. This problem assumes fully connected processors and ignores contention on the communication links. However, as arbitrary processor network (APN), communication contention has a strong influence on the execution time of a parallel application. In this paper, we propose multi-objective genetic algorithm to solve task scheduling...