METHOD OF DNA COMPUTING AND ITS APPLICATION TO GROUP MANAGEMENT

Junzo Watada
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Junzo Watada: Waseda University, Japan

Chapter 9 in Advances in Doctoral Research in Management, 2008, pp 175-192 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThe objective of this chapter is to illustrate the method of DNA computing and based on this understanding, to explain the application to group controlling of elevators.Many non-deterministic polynomial time (NP) complete problems are solved using heuristic and approximate methods instead of providing a complete solution or mathematical optimal approaches. The central reason comes from the huge computation time needed to solve such combinatorial problems by means of a conventional silicon computer based on von Neumann's architecture. To solve such NP complete problems, this chapter provides an alternative and innovative method based on nano size of DNA to obtain infinitively in a life such as silicon. This chapter is an introductory explanation.The group management is treated as an example of its application. Inefficient situations have been encountered such that all elevators are moving in the same direction or that all elevators arrive at the same floor even during rush hours in the morning. To resolve such situations all elevators should be controlled to assign the best elevator to passengers according to time-to-time change of passengers. The group control system is employed in selection of driving patterns according to the change of traffic volumes or driving management in accidents. Such a group control realises comfortable, safe, and economical management of elevators. The objective of this chapter is to apply DNA computing to calculate complex and huge combinatorial problems of a group of elevators and huge number of floors. The optimal solution will be presented to the group control of elevators on the basis of the DNA computing.

Keywords: Doctoral; Research; Management Methodology; Data; Analysis; Paradigm; Modeling; International; Management Theory; Statistics; Market Survey (search for similar items in EconPapers)
JEL-codes: F1 (search for similar items in EconPapers)
Date: 2008
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