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6 Result(s)

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  1. No Access

    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...

    Shree Ram Pandey, Rituparna Datta… in Swarm, Evolutionary, and Memetic Computing… (2020)

  2. No Access

    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...

    Palash Pal, Rituparna Datta, Deepak Rajbansi… in Swarm, Evolutionary, and Memetic Computing… (2020)

  3. No Access

    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...

    Rituparna Datta, Kalyanmoy Deb, Jong-Hwan Kim in Neural Computing and Applications (2019)

  4. No Access

    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...

    Rituparna Datta, Kalyanmoy Deb in Evolutionary Multi-Criterion Optimization (2011)

  5. No Access

    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...

    Rituparna Datta in Simulated Evolution and Learning (2010)

  6. No Access

    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...

    Kalyanmoy Deb, Swanand Lele, Rituparna Datta in Advances in Computation and Intelligence (2007)