Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...

To satisfy the demand for higher performance, modern processors are designed with a high degree of speculation. While speculation enhances performance, it burns power unnecessarily. The cache, store queue, and load queue are accessed associatively before a matching entry is determined. A significant amount of power is wasted to search entries that are not picked. Modern processors speculatively...

Imagine a number of processes all need to use a particular resource for a period of time. Each process i specifies a starting time s(i) and a finishing time f(i) between which it needs to continuously occupy the resource. The resource cannot be shared by two processes at any instance. One is required to design a scheduler which chooses a subset of these processes so that 1) there is no time con...

Gafarov et al. [6] have recently presented an O(n) time dynamic programming algorithm for a single machine scheduling problem to maximize the total job tardiness. We reduce this problem in O(n log n) time to a problem of unconstrained minimization of a function of 0-1 variables, called half-product, for which a simple O(n) time dynamic programming algorithm is known in the literature.

One of the most known applications of Discrete Optimization is on scheduling. In contrast, one of the most known applications of Continuous Nonlinear Optimization is on the control of dynamic systems. In this paper, we combine both views, solving scheduling problems as dynamic systems, modeled as discrete-time nonlinear optimal control problems with state and control continuous variables subjec...

In this paper, we propose a new solution for dynamic task scheduling in distributed environment. We argue that a function is existed in the items: execution time, the size of data and the algorithm, therefore we can deduce the execution time of a data mining task from the corresponding the size of data and algorithm. We adopt the sampling method for process the tasks scheduling in distributed d...

We present an approach to computing cyclic schedules online and in real time, while attempting to maximize a quality-of-service metric. The motivation is the detection of RF emitters using a schedule that controls the scanning of disjoint frequency bands. The problem is NP-hard, but it exhibits a so-called phase transition that can be exploited to rapidly find a “good enough” schedule. Our appr...

This paper presents several local search meta-heuristics for the problem of scheduling a single machine to minimise total weighted tardiness. A genetic algorithm for the static single machine total weighted tardiness problem is presented, and a multi-start version named metaGA is proposed. The obtained computational results permit to conclude about their efficiency and effectiveness. The resolu...

Feldmann, A., J. Sgall and S.-H. Teng, Dynamic scheduling on parallel machines, Theoretical Computer Science 130 (1994) 49-72. We study the problem of on-line job-scheduling on parallel machines with different network topologies. An on-line scheduling algorithm schedules a collection of parallel jobs with known resource requirements but unknown running times on a parallel machine. We give an O(...

Many time-critical applications require dynamic scheduling with predictable performance. Tasks corresponding to these applications have deadlines to be met despite the presence of faults. In this paper, we propose a technique called dynamic grouping, to be used with backup overloading in a primary-backup based fault-tolerant dynamic scheduling algorithm in multiprocessor real-time systems. In d...