Minimizing a cost function under a set of combinatorial constraints is a fundamental, yet challenging problem in AI. Fortunately, in various real-world applications, the set of constraints describing the problem structure is much less susceptible to change over time than the cost function capturing user’s preferences. In such situations, compiling the set of feasible solutions during an offline...

Four heuristic algorithms are developed for solving the generalized version of tardiness flow shop problems. We consider the generalized tardiness flow shop model with minimization of the total tardiness as its performance measure. We modify the concept of cost over time (COVERT) for the generalized version of the flow shop tardiness model and employ this concept for developing four algorithms....

In order to model capacitated location–allocation problem with fuzzy demands, three types of fuzzy programming models – fuzzy expected cost minimization model, fuzzy a-cost minimization model, and credibility maximization model – are proposed according to different decision criteria. For solving these models, some hybrid intelligent algorithms are also designed. Finally, several numerical exper...

recovery of used products is receiving much attention recently due to growing environmental concerns.in this paper, we address the carbon footprint basedon problem arising in closed-loop supply chain where returned products are collected from customers. these returned products can either be disposed or be remanufactured to be sold as new ones again. here, we formulate a comprehensive closed-loo...

Determining shape from stereo has often been posed as a global minimization problem. Once formulated, the minimization problems are then solved with a variety of algorithmic approaches. These approaches include techniques such as dynamic programming min-cut and alpha-expansion. In this paper we show how an algorithmic technique that constructs a discrete spatial minimal cost surface can be brou...

Power system must be operated in such a way that both real and reactive powers are optimized simultaneously. Reactive powers should be optimized to provide better voltage profile as well as to reduce system losses. The four objectives of minimization of fuel cost, minimization of emission, minimization of losses and increasing stability by minimizing system stability index, these are conflictin...

This paper aims at studying a semi-blind channel estimation scheme based on the subspace method or a carefully weighted linear prediction approach. The corresponding (composite) semi-blind cost functions result from a linear combination of the training-based cost function and a blind cost function. For each blind method, we show how to calculate the asymptotic estimation error. Therefore, by mi...

A shared secret, conference key, must be established among members to securely communicate among them. The Diffie-Hellman is often used for the conference key establishment. In a heterogenous network, the participants have different resources. Therefore, different burden should be placed on different participants. However, most protocols did not address this problem. Wade Trappe et. al. address...

The paper presents a computer-aided methodology for economic optimization of industrial plants safety. The method is based on the minimization of total safety-related cost including investment, operating expenses of adopted safety measures, and expected monetary loss from accidents. The objective function minimization is pursued resorting to a genetic algorithm which selects the best mix of saf...