the product rate variation problem minimizes the variation in the rate at which different models of a common base product are produced on the assembly lines with the assumption of negligible switch-over cost and unit processing time for each copy of each model. the assumption of significant setup and arbitrary processing times forces the problem to be a two phase problem. the first phase determ...

new product development (npd) is one of the key factors for achieving competitive advantage and maintaining firm growth. therefore, given the importance of this type of projects, this paper is an endeavor to make these projects more successful by effectively managing their risks in the conceptual design phase of new product development. for this purpose, a multi-objective model, with three obje...

Although significant private investment is absorbed in different sectors of power systems, transmission sector is still suffering from appropriate private investment. This is because of the pricing policies of transmission services, tariffs, and especially for investment risks. Investment risks are due to the uncertain behaviour of power systems that discourage investors to invest in the transm...

This study presents an optimal framework for the operation of integrated energy systems using demand response programs. The main goal of integrated energy systems is to optimally supply various demands using different energy carriers such as electricity, heating, and cooling. Considering the power market price, this work investigates the effects of multiple energy storage devices and demand res...

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...

This paper deals with a network of computing agents aiming to solve an online optimization problem in distributed fashion, i.e., by means local computation and communication, without any central coordinator. We propose the gradient tracking adaptive momentum estimation (GTAdam) algorithm, which combines mechanism first second order estimates gradient. The algorithm is analyzed setting for stron...