This research presents an application of the relatively new approach of ant colony optimization (ACO) to address a production-sequencing problem when two objectives are present Ð simulating the arti®cial intelligence agents of virtual ants to obtain desirable solutions to a manufacturing logistics problem. The two objectives are minimization of setups and optimization of stability of material u...

Today’s complex embedded systems function in varying operational conditions. The control software adapts several control variables to keep the operational state optimal with respect to multiple objectives. There exist well-known techniques for solving such optimization problems. However, current practice shows that the applied techniques, control variables, constraints and related design decisi...

In WSNs, energy conservation is the primary goal, while throughput and delay are less important. This results in a tradeoff between performance (e.g., throughput, delay, jitter, and packet-loss-rate) and energy consumption. In this paper, the problem of energy-efficient MAC protocols in WSNs is modeled as a game-theoretic constraint optimization with multiple objectives. After introducing incom...

Design, implementation and operation of solar thermal electricity plants are no more an academic task, rather they have become a necessity. In this paper, we work with power industries to formulate a multiobjective optimization model and attempt to solve the resulting problem using classical as well as evolutionary optimization techniques. On a set of four objectives having complex trade-offs, ...

The design of supervised learning systems for classification require finding a trade-off among a number of competing performance criteria. A common approach is to optimize an overall objective derived from the individual performance objectives. Such a simplified approach promises only for the chosen performance metric when evaluated over the training samples, yet does not make any guarantee on ...