Most of the engineering problems are modeled as evolutionary multiobjective optimization problems, but they always ask for only one best solution, not a set of Pareto optimal solutions. The decision maker’s subjective information plays an important role in choosing the best solution from several Pareto optimal solutions. Generally, the decision-making processing is implemented after Pareto opti...

Many distributions have been used as lifetime models. In this article, we propose a new threeparameter Weibull–Pareto distribution, which can produce the most important hazard rate shapes, namely, constant, increasing, decreasing, bathtub, and upsidedown bathtub. Various structural properties of the new distribution are derived including explicit expressions for the moments and incomplete momen...

Pareto-optimal solutions are one of the most important and well-studied solution concepts in multi-objective optimization. Often the enumeration of all Pareto-optimal solutions is used to filter out unreasonable trade-offs between different criteria. While in practice, often only few Pareto-optimal solutions are observed, for almost every problem with at least two objectives there exist instanc...

In this paper, several new set quality metrics are introduced that can be used to evaluate the ‘‘goodness’’ of an observed Pareto solution set. These metrics, which are formulated in closed-form and geometrically illustrated, include hyperarea difference, Pareto spread, accuracy of an observed Pareto frontier, number of distinct choices and cluster. The metrics should enable a designer to eithe...

Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface methods in combination with evolutionary algorithms could accelerate the determination of the Paret...

Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface methods in combination with evolutionary algorithms could accelerate the determination of the Paret...

Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when scoring schemes A and B can correctly evaluate the search space via dynamic programming, then so ca...

Self-optimization enables technical systems to adapt their behavior to varying environmental conditions and changing system settings. Objective functions serve as evaluation criteria for the system behavior. In this paper we propose a hierarchical control approach of an objective-based Pareto controller. We separate the processes of optimization and control. First, we use multiobjective optimiz...

in this paper, we derive the exact analytical expressions for the shannon entropy of generalized orderstatistics from pareto-type and related distributions.

In this study, response surface models (RSMs) based on limited data are developed. Experimental cutting force data for the flat end milling process are employed to build these models. Four RSM models are developed in terms of process variables. The first model is used to build the mean cutting force. Similarly, the second, third and fourth models are used to build models for the variance, skewn...