Title: Multi-criteria probability collectives

Authors: Neha S. Patankar; Anand J. Kulkarni; Kang Tai; T.D. Ghate; A.R. Parvate

Addresses: Department of Operations Research, North Carolina State University, 2366 Champion Court, Raleigh, NC 27606, USA ' Odette School of Business, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada ' School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore ' Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, 2039 Engineering Research Facility, 842 W. Taylor Street, Chicago, Illinois 60607, USA ' Optimization and Agent Technology (OAT) Research Lab, Maharashtra Institute of Technology, 124 Paud Road, Pune 411038, India

Abstract: The nature-/bio-/socio-inspired optimisation techniques can efficiently handle unconstrained problems; however, their performance gets significantly affected when applied for solving constrained problems. This paper proposes a variation of the distributed optimisation multi-agent system (MAS) approach of probability collectives (PC) in collective intelligence domain referred to as multi-criteria probability collective (MCPC). In this approach, the constraints are efficiently handled by giving equal importance as the objective function. It is validated by solving a variety of constrained test problems including tension/compression spring design problem and pressure vessel design problem. The solution to these problems proves that the MCPC approach can be applied to a variety of complex practical/real world problems.

Keywords: multicriteria probability collectives; MCPCs; multi-agent systems; MAS; agent-based systems; collective intelligence; COIN; constrained test problems; constraint handling; tension; compression; spring design; pressure vessel design.

DOI: 10.1504/IJBIC.2014.066975

International Journal of Bio-Inspired Computation, 2014 Vol.6 No.6, pp.369 - 383

Received: 23 May 2014
Accepted: 04 Oct 2014
Published online: 24 Jan 2015 *

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