this paper presented a mixed integer programming for integrated scheduling and process planning. the presented process plan included some orders with precedence relations similar to multiple traveling salesman problem (mtsp), which was categorized as an np-hard problem. these types of problems are also called advanced planning because of simultaneously determining the appropriate sequence and m...

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...

The classical identical parallel machine scheduling problem can be stated as follows: Given n jobs and m machines, the problem is to assign each job on one of the identical machines during a fixed processing time so that the schedule that optimizes a certain performance measure is obtained. Having numerous potential applications in real life, in recent years, various research works have been ca...

On-chip resource sharing among sibling cores causes resource contention on Chip Multiprocessors (CMP), considerably degrading program performance and system fairness. Job co-scheduling attempts to alleviate the problem by assigning jobs to cores appropriately. Despite many heuristics-based empirical explorations, studies on optimal co-scheduling and its inherent complexity start only recently, ...

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 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...

Today, cloud computing has provided a suitable platform to meet the needs of users. One most important challenges facing is Dynamic Resource Allocation (DSA), which in NP-Hard class. goals DSA utilization resources efficiently and maximize productivity. In this paper, an improved Firefly algorithm based on load balancing optimization introduced solve problem called IFA-DSA. addition workloads b...

Task scheduling in highly elastic and dynamic processing environments such as cloud computing have become the most discussed problem among researchers. algorithms are responsible for allocation of tasks resources their execution, an inefficient task algorithm results under-or over-utilization resources, which turn leads to degradation services. Therefore, proposed work, load balancing is consid...

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...