Analysis on Multi-objective Optimization Problem Techniques

  • Aditi JaiswalEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 755)


In past few years, Web-based application and services are growing rapidly and this growing demands needs different Quality of Services (QoS) requirements for efficient use of such web-based services. The purpose behind utilizing these application resources could be tarnished if the fundamental communication network does not fulfill the QoS requirements. However, different applications have distinct QoS necessities as each application have different priorities. The main concern is to come across such solution which will optimize the network not in the terms of minimum number of hops but in terms of Qos parameters of network, relies upon application running over that network. This issue comes under Multi-objective Optimization Problem (MOOP) and Genetic Algorithm (GA) is one of the techniques which can possibly control numerous parameters all together, and hence GA is applied to solve MOOP, which can enhance the QoS. This paper surveys the various MOOP techniques and then gives the best solution among them.


Multi-objective optimization problem Evolutionary algorithms Quality of service (qos) Genetic algorithm (ga) 


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentMaulana Azad National Institute of TechnologyBhopalIndia

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