Multicriteria Choice of Night Vision Devices Considering the Impact of Their Performance Parameters

The problem of technical devices evaluation and choosing is not easy decision making process. The technological development and the availability of many different technical solutions with different performance parameters specify complex combinatorial choice problems. The night vision devices (NVD) have become quite popular recently and are an example of complex technical choice with conflicting performance parameters. The paper describes important NVD parameters that should be considered and a multicriteria optimization approach for smart NVD choice. The proposed approach uses popular weighted sum method to comply with different user preferences by defining relative weights among NVD parameters considered as objective functions. The practical applicability of the proposed approach has been demonstrated by some case study examples of choosing night vision goggles satisfying different user preferences. Real set of devices offered on Internet are used to formulate and solve optimization tasks reflecting user’s preferences. The proposed multicriteria choice approach can be used for all types of night vision devices and other technical devices also to make a smart choice corresponding to decision-makers preferences and restrictions.

[1]  Mohammad A. Karim,et al.  Study of field-of-view overlap for night vision applications , 1992, Proceedings of the IEEE 1992 National Aerospace and Electronics Conference@m_NAECON 1992.

[2]  Keith D Higginbotham.  Effect of Using High Signal-to-Noise Image Intensifier Tubes on Night Vision Goggle (NVG) Aided Visual Acuity , 2006 .

[3]  R. Wiley,et al.  Visual Acuity and Stereopsis with Night Vision Goggles , 1989 .

[4]  I. Kim,et al.  Adaptive weighted sum method for multiobjective optimization: a new method for Pareto front generation , 2006 .

[5]  Neil A. Dodgson,et al.  Variation and extrema of human interpupillary distance , 2004, IS&T/SPIE Electronic Imaging.

[6]  James D. Whiteley,et al.  The Effect of Signal-to-Noise Ratio on Visual Acuity Through Night Vision Goggles , 1991 .

[7]  Warren S. Torgerson,et al.  Human Off-Road Mobility, Preference, and Target-Detection Performance with Monocular, Biocular, and Binocular Night Vision Goggles. , 1996 .

[8]  Sharon A. Dixon,et al.  Visual acuity versus field of view and light level for night vision goggles (NVGs) , 1994, Defense, Security, and Sensing.

[9]  Andrzej Osyczka,et al.  Multicriterion optimization in engineering with FORTRAN programs , 1984 .

[10]  I. Y. Kim,et al.  Adaptive weighted-sum method for bi-objective optimization: Pareto front generation , 2005 .

[11]  Marc Parizeau,et al.  Human-competitive lens system design with evolution strategies , 2008, Appl. Soft Comput..

[12]  H. L. Task.  Night Vision Devices and Characteristics , 1992 .

[13]  Harry L. Task,et al.  Methods for Measuring Characteristics of Night Vision Goggles , 1993 .

[14]  G. Weigert,et al.  MULTI OBJECTIVE DECISION MAKING – SOLUTIONS FOR THE OPTIMIZATION OF MANUFACTURING PROCESSES , 2000 .