The prevalent approach to the treatment of processing time uncertainties in production scheduling problems is through the use of probabilistic models. Apart from requiring detailed information about probability distribution functions, this approach also has the drawback that the computational expense of solving these models is very high. In this work, we present a non-probabilistic treatment of...

In the presence of imprecise management targets, staff preferences, and patients’ expectations, the healthcare staff scheduling problem becomes complicated. The goals, preferences, and client expectations, being humanistic, are often imprecise and always evolving over time. We present a fuzzy genetic algorithm (FGA) approach for addressing healthcare staff scheduling problems in fuzzy environme...

Abstract. In this paper, a new procedure for project scheduling called 'fuzzy cash flow weight' and 'fuzzy discounted cash flow weight' is studied with the aid of generalized trapezoidal fuzzy numbers. A new ranking procedure namely 'SD of PILOT' (Shortest Distance of the Point of Intersection of Legs of Trapezium) is proposed to find out the output of the above said notion. Relevant arithmetic...

The classical analysis of realtime systems tries to ensure that the instance of every task finishes before its absolute deadline (strict guarantee). The probabilistic approach tends to estimate the probability that it will happen. The deterministic timed behavior is an important parameter for analyzing the robustness of the system. Most of related works are mainly based on the determinism of ti...

The Fuzzy set theory has been applied in many fields such as management, engineering and almost in every business enterprise as well as day to day activities. Ordering fuzzy numbers plays an important role in approximate reasoning, optimization, forecasting, decision making, risk analysis, controlling, scheduling and various other usages in our day to day activities. This paper describes a rank...

Imprecise input data imposes additional challenges to grid scheduling. This paper introduces a novel scheduler based on fuzzy optimization called IP-FULL-FUZZY which considers uncertainties of both application demands and of resource availability. The effectiveness of the proposed scheduler is compared to those of a non-fuzzy scheduler as well as to those of a fuzzy scheduler which considers on...

This paper analyses the schedulability of realtime systems with uncertain knowledge. Fuzzy numbers are used to model parameters describing tasks, providing information about observation of the tasks deadlines at early phases of development. In this paper fuzzy schedulability and a fuzzy optimality criteria are defined and the fuzzy optimality of Deadline Monotonic Scheduling algorithm is proved...

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...