Engineering Analytics for selection of the Best Solution

Selection of the best possible option when many alternatives are available is vital in decision-making process. In addition, the selection process becomes more complicated when the definition of ‘Best’ option changes with conditions and time – the problem becomes the optimization problem.

With Engineering Analytics, CAPGEMINI P&ES (Product & Engineering Solutions) has developed unique expertise to solve such problems in optimization in diverse fields using various advanced techniques. Several client case studies can be solved using this framework for operations planning, scheduling, and maintenance.  The framework provide ready to use evolutionary search algorithms such as Simulated Annealing and Genetic Algorithm. The optimization framework using these evolutionary algorithms proposed by CAPGEMINI is expected to provide high degree of advantages in turnaround time for problems in optimization.

Read more about this optimization framework with the illustrations in the whitepaper, here.

Umesh Hivarkar


Multidisciplinary skills with a unique combination of scientific R&D, academics, and industry profile. Doctoral research in fiber optics & sensors, Instrumentation, Integrated optics, and Modeling & Simulation. Spanning over 24+ years of application-oriented R&D and multi-sector industrial experience. Expertise in Engineering Analytics, automation, and control, and Advanced Intelligent Systems. Known for innovative solutioning and industrialization of cutting edge technologies.

More on Umesh Hivarkar.

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