We explore the potential of adding objective functions to OCL operation contracts. If an operation contract includes an objective function, the operation has the obligation to yield results that make the objective function assume an optimal value. Thus, an objective function expresses a preference among the possible operation results that conform to the postconditions of the operation contract ...

In order to incorporate fuzzy goals and constraints in model predictive control, this control technique have recently been integrated with fuzzy decision making. The goals and the constraints of the control problem are combined by using a decision function from the theory of fuzzy sets. This technique have been studied for single-input single-output processes. This paper extends this approach f...

Many randomized algorithms can be derandomized efficiently using either the method of conditional expectations or probability spaces with low independence. A series of papers, beginning with work by Luby (1988), showed that in many cases these techniques can be combined to give deterministic parallel (NC) algorithms for a variety of combinatorial optimization problems, with low time- and proces...

In multiple objective programs [MOP], application functions are established to measure the degree of fulfillment of the decision maker’s requirements (achievement of goals, nearness to an ideal point, satisfaction, etc.) about the objective functions (see e.g. [7, 24]) and are extensively used in the process of finding ”good compromise” solutions. In [6] we demonstrated that the use of interdep...

Background: Interleukin 6 (IL-6) functions as both a pro-inflammatory cytokine and an anti-inflammatory cytokine. Objective: To evaluate the levels of IL-6 in patients with multiple organ dysfunction syndrome (MODS). Methods: Level of IL-6 was assessed and recorded for 14 days subsequent to the injury in 161 multiple trauma patients. MODS were diagnosed using Marshal Score. Injury Severity Scor...

Conventional paradigms of machine learning assume all the training data are available when learning starts. However, in lifelong learning, the examples are observed sequentially as learning unfolds, and the learner should continually explore the world and reorganize and refine the internal model or knowledge of the world. This leads to a fundamental challenge: How to balance long-term and short...

The number partitioning problem is to divide a set of integers into a collection of subsets, so that the sum of the numbers in each subset are as nearly equal as possible. There are at least three natural objective functions for number partitioning. One is to minimize the largest subset sum, another is to maximize the smallest subset sum, and the third is to minimize the difference between the ...