These are important objectives for maximizing energy yield while minimizing costs.
Objectives for maximizing the effectiveness of a human robot system are presented, which capture these coupled relationships, and reliability parameters are proposed to characterize unplanned interventions between a human and robot.
Also, a comparison of cycles modeling results is carried out in optimum conditions according to different optimization which consist thermodynamic, economic and thermo-economic objective functions for maximizing exergy efficiency, minimizing specific investment cost and applying a multi-objective function in order to maximize exergy efficiency and minimize specific investment cost, respectively.
The specific energy absorption (SEA) is used as a single optimization objective function for maximizing energy absorption and minimizing mass.
First, we need to establish the optimal objective function for maximizing the throughput gain with constraints of QoS and transmit power.
Multi objective optimization for maximizing the copper removal efficiency and minimizing the energy consumption was carried out using genetic algorithm (GA) over the ANN model.
To solve the ε-FMOOP, each fuzzy objective functions for maximizing synthesis rate can be quantified by eliciting the following membership function: (21) η i (f i ) = 0 f i L B > f i, d i f i L B ≤ f i ≤ f i U B, 1 f i > f i U B, i ∈ Σ O, where d i is a strictly monotonically increasing function for evaluating the degree of satisfaction.
Multi-objective optimization for maximizing the final conversion and minimizing the equipment cost and energy consumption concluded that optimizing the reaction volume and circulation ratios could obtain Pareto optimal set for selecting preferred design parameters by using non-dominated sorting genetic algorithm (NSGA-II).
Their study solves two bi-objective optimization problems for maximizing DAHPS and PEPC flux ratios and maximizing DAHPS and SERS flux ratios, respectively, to determine the optimal gene manipulation strategies.
In this paper, we design an analytically and experimentally better online energy and job scheduling algorithm with the objective of maximizing net profit for service providers in green data centers.
