Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximize pseudopotential softness while maintaining high accuracy transferability. To accomplish this, develop formulation in which simultaneously maximized, with determined by the ability reproduce all-electron energy diff...

Topology optimization (TO), which is a design technique that does not require parameters, has been attracting attention. TO high degree of freedom and can obtain novel shape suitable for desired purposes. However, the characteristics obtained may be greatly damaged due to uncertainty such as variations in material properties. Also, when multi-objective considered, an increase calculation load b...

Growing concern in the management of energy due to the increasing energy costs, has forced managers to optimize the amount of energy required to provide products and services. This research integrates an energy-based resource investment project-scheduling problem (RIP) under a multi-skilled structure of the resources. The proposed energy based multi skilled resource investment problem (EB-MSRIP...

A multi-condition multi-objective optimization method that can find Pareto front over a defined condition space is developed for the first time using deep reinforcement learning. Unlike conventional methods which perform at single condition, present learns correlations between conditions and optimal solutions. The exclusive capability of examined in solutions novel modified Kursawe benchmark pr...

In this paper multi-objective genetic algorithms were employed for Pareto approach optimization of turboprop engines. The considered objective functions are used to maximize the specific thrust, propulsive efficiency, thermal efficiency, propeller efficiency and minimize the thrust specific fuel consumption. These objectives are usually conflicting with each other. The design variables consist ...

The paper is aimed to the multi-objective optimization of wire multi-band antennas. Antennas are numerically modeled using time-domain integral-equation method. That way, the designed antennas can be characterized in a wide band of frequencies within a single run of the analysis. Antennas are optimized to reach the prescribed matching, to exhibit the omni-directional constant gain and to have t...

Single objective evolutionary constrained optimization has been widely searched and researched by plethora of researchers in last two decades. On the other hand, multi-objective constraint handling using evolutionary algorithms has not been actively proposed. However, real-world multi-objective optimization problems consist of one or many non-linear and non-convex constraints. In the present wo...

Many-objective optimization problems (MaOPs) are challenging in scientific research. Research has tended to focus on algorithms rather than algorithm frameworks. In this paper, we introduce a projection-based evolutionary algorithm, MOEA/PII. Applying the idea of dimension reduction and decomposition, it divides objective space into projection plane free dimension(s). The balance between conver...

Objectives . A frequently used method for obtaining Pareto-optimal solutions is to minimize a selected quality index under restrictions of the other indices, whose values are thus preset. For scalar objective function, global minimum sought that contains restricted indices as penalty terms. However, landscape such function has steep-ascent areas, which significantly complicate search minimum. T...