Simultaneous Optimization of Customer Satisfaction and Cost Function by Nature Inspired Computing

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 15)

Abstract

When optimizing multi-dimensional non-linear problems the optimal solution in technical terms can be found by heuristic methods. It seems that human thinking does not work properly with the mathematical processing: human decision-makers tend to reject options that represent extreme values in the set of parameters and are not able to handle many system parameters at the same time. The paper investigates the best possible way for modeling the human thinking, comparing bacterial memetic algorithm and particle swarm optimization in fuzzy environment.

Keywords

Particle Swarm Optimization Customer Satisfaction Memetic Algorithm Human Thinking Simultaneous Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of AutomationSzéchenyi István UniversityGyőrHungary
  2. 2.Department of Logistics and ForwardingSzéchenyi István UniversityGyőrHungary

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