In this chapter, we present a survey of constraint-handling techniques based on evolutionary multiobjective optimization concepts. We present some basic definitions required to make this chapter self-contained, and then we introduce the way in which a global (single-objective) nonlinear optimization problem is transformed into an unconstrained multiobjective optimization problem. A taxonomy of ...

While evolutionary computing inspired approaches to multi-objective optimization have many advantages over conventional approaches; they generally do not explicitly exploit directional/gradient information. This can be inefficient if the underlying objectives are reasonably smooth, and this may limit the application of such approaches to real-world problems. This paper develops a local framewor...

Fuzzy based stochastic algorithms for solving Multi-objective Reactive Power Optimization (MORPO) problem including FACTS devices is presented in this paper. The Multi-Objective Reactive Power Optimization problem is formulated as a nonlinear constrained multi-objective optimization problem where the active power, voltage deviation and investment cost has to be minimized simultaneously. Fuzzy l...

this paper presents a clear monograph on the optimization of thermal instability resistance of the fg (functionally graded) flat structures. for this aim, two fg flat structures, namely an fg beam and an fg circular plate, are considered. these structures are assumed to obey the first-order shear deformation theory, three-parameters power-law distribution of the constituents, and clamped bounda...

in today's globalization, an effective integration of production and distribution plans into a unified framework is crucial for attaining competitive advantage. this paper addresses an integrated multi-product and multi-time period production/distribution planning problem for a two-echelon supply chain subject to the real-world variables and constraints. it is assumed that all transportations a...

this paper presents an innovative active power filter design method to simultaneously compensate the current harmonics and reactive power of a nonlinear load. the power filter integrates a passive power filter which is a rl low-pass filter placed in series with the load, and an active power filter which comprises an rl in series with an igbt based voltage source converter. the filter is assumed...

Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained mul...

Multi-modal multi-objective optimization problems (MMMOPs) have multiple subsets within the Pareto-optimal Set, each independently mapping to same Pareto-Front. Prevalent evolutionary algorithms are not purely designed search for solution subsets, whereas, MMMOPs demonstrate degraded performance in objective space. This motivates design of better addressing MMMOPs. The present work identifies c...

In this paper, a new method of H filtering for Lipschitz nonlinear systems is proposed in the form of an LMI optimization problem. The proposed filter has guaranteed decay rate (exponential convergence) and is robust against unknown exogenous disturbance. In addition, thanks to the linearity of the proposed LMIs in the admissible Lipschitz constant, it can be maximized via LMI optimization. Th...

This paper considers the problem of robust reconstruction of simultaneous actuator and sensor faults for a class of uncertain Takagi–Sugeno nonlinear systems with unmeasurable premise variables. The proposed fault reconstruction and estimation design method with H∞ performance is used to reconstruct both actuator and sensor faults when the latter are transformed into pseudo-actuator faults by i...