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Article
Failing And Not Falling (F&!F): Data-Enabled Classification Learning of Aircraft Accidents and Incidents
Journey by aircraft is the only option for long-distance transportation and also one of the frequently used modes of transportation of passengers. As a result, safety of passengers and efficiency of the aircra...
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Chapter and Conference Paper
Evolutionary Bi-objective Optimization and Knowledge Extraction for Electronic and Automotive Cooling
The heat sink is one of the most widely used devices for thermal management of electronic devices and automotive systems. The present study approaches the design of the heat sink with the aim of enhancing thei...
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Chapter and Conference Paper
A Neural Net Based Prediction of Sound Pressure Level for the Design of the Aerofoil
Aerofoil self-noise can affect the performance of the overall system. One of the main goals of aircraft design is to create an aerofoil with minimum weight, cost, and self-noise, satisfying all design requirem...
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Article
CHIP: Constraint Handling with Individual Penalty approach using a hybrid evolutionary algorithm
Constraint normalization ensures consistency in scaling for each constraint in an optimization problem. Most constraint handling studies only address the issue to deal with constraints and use problem informat...
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Article
Topology optimization of compliant structures and mechanisms using constructive solid geometry for 2-d and 3-d applications
This research focuses on the establishment of a constructive solid geometry-based topology optimization (CSG-TOM) technique for the design of compliant structure and mechanism. The novelty of the method lies i...
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Book
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Chapter
Multi-objective Optimization: Classical and Evolutionary Approaches
Problems involving multiple conflicting objectives arise in most real world optimization problems. Evolutionary Algorithms (EAs) have gained a wide interest and success in solving problems of this nature for t...
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Chapter
Practical Applications in Constrained Evolutionary Multi-objective Optimization
Constrained optimization is applicable to most real world engineering science problems. An efficient constraint handling method must be robust, reliable and computationally efficient. However, the performance ...
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Article
Uniform adaptive scaling of equality and inequality constraints within hybrid evolutionary-cum-classical optimization
The holy grail of constrained optimization is the development of an efficient, scale invariant and generic constraint handling procedure. To address these, the present paper proposes a unified approach of cons...
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Article
A piezoelectric model based multi-objective optimization of robot gripper design
The field of robotics is evolving at a very high pace and with its increasing applicability in varied fields, the need to incorporate optimization analysis in robot system design is becoming more prominent. Th...
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Book
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Chapter and Conference Paper
Unified Minimalistic Modeling of Piezoelectric Stack Actuators for Engineering Applications
Piezoelectric (PZ) actuator is widely recognized for its high precision and displacement accuracy even at nanometer ranges. A minimalistic model is proposed in the present work, for PZ stack actuators. In the ...
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Chapter and Conference Paper
Dual Multiobjective Quantum-Inspired Evolutionary Algorithm for a Sensor Arrangement in a 2D Environment
This paper proposes dual multiobjective quantum-inspired evolutionary algorithm (DMQEA) for a sensor arrangement problem in a 2D environment. DMQEA has a dual stage of dominance check by introducing secondary ...
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Chapter
Evolutionary Constrained Optimization: A Hybrid Approach
The holy grail of constrained optimization is the development of an efficient, scale invariant, and generic constraint-handling procedure in single- and multi-objective constrained optimization problems. Const...
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Chapter and Conference Paper
A Bi-objective Based Hybrid Evolutionary-Classical Algorithm for Handling Equality Constraints
Equality constraints are difficult to handle by any optimization algorithm, including evolutionary methods. Much of the existing studies have concentrated on handling inequality constraints. Such methods may o...
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Chapter and Conference Paper
Constrained Engineering Design Optimization Using a Hybrid Bi-objective Evolutionary-Classical Methodology
Constrained engineering design optimization problems are usually computationally expensive due to non-linearity and non convexity of the constraint functions. Penalty function methods are found to be quite pop...
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Chapter and Conference Paper
A Hybrid Evolutionary Multi-objective and SQP Based Procedure for Constrained Optimization
In this paper, we propose a hybrid reference-point based evolutionary multi-objective optimization (EMO) algorithm coupled with the classical SQP procedure for solving constrained single-objective optimization...
