This paper demonstrates that the self-adaptive technique of Differential Evolution (DE) can be simply used for solving a multiobjective optimization problem where parameters are interdependent. The real-coded crossover and mutation rates within the NSGA-II have been replaced with a simple Differential Evolution scheme, and results are reported on a rotated problem which has presented difficulti...

The evolutionary approach in the design optimisation of MEMS is a novel and promising research area. The problem is of a multi-objective nature; hence, multi-objective evolutionary algorithms (MOEA) are used. The literature shows that two main classes of MOEA have been used in MEMS evolutionary design Optimisation, NSGA-II and MOGA-II. However, no one has provided a justification for using eith...

The Software Cost Estimation is very important task for completing the project successfully. The estimation in software development depends on various factors especially on cost and effort factors for which further AI (Artificial Intelligence) and Algorithmic models have been put into usage. This paper aims to discuss the methods for calculating the effort by using meta-heuristic algorithms for...

This study presents a methodology for quantifying the tradeoffs between sampling costs and local concentration estimation errors in an existing groundwater monitoring network. The method utilizes historical data at a single snapshot in time to identify potential spatial redundancies within a monitoring network. Spatially redundant points are defined to be monitoring locations that do not apprec...

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative ...

In multiobjective particle swarm optimization (MOPSO), the global-best is randomly selected for each population from a nondominated solution set. However, this Roulette wheel-based global selection ineffective convergence and diversity when problem has numerous decision variables or large number of candidates. Thus, study proposes cluster-based MOPSO (CMOPSO). CMOPSO, similarities between parti...

Abstract In this study, a model for the selection of investment portfolios is proposed with three objectives. addition to traditional objectives maximizing profitability and minimizing risk, maximization social responsibility also considered. Moreover, purpose controlling transaction costs, limit placed on number assets selection. To best our knowledge, specific has not been considered in liter...

The performance of voltage stability indices in the multiobjective optimal power flow modern systems is presented this work. Six indices: Voltage Collapse Proximity Index (VCPI), Line Stability (LVSI), (Lmn), Fast (FVSI), Factor (LQP), and Novel (NLSI) were considered as case studies on a modified IEEE 30-bus consisting thermal, wind, solar hybrid wind-hydro generators. A evaluation using mayfl...

This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimization tool for solving this problem. The proposed methodology is based on a new variant of ant colony optimization (ACO) specialized in multi-objective o...