×

zbMATH — the first resource for mathematics

Comparison of weights in TOPSIS models. (English) Zbl 1066.90054
Summary: TOPSIS is a multiple criteria method to identify solutions from a finite set of alternatives based upon simultaneous minimization of distance from an ideal point and maximization of distance from a nadir point. TOPSIS can incorporate relative weights of criterion importance. This paper reviews several applications of TOPSIS using different weighting schemes and different distance metrics, and compares results of different sets of weights applied to a previously used set of multiple criteria data. Comparison is also made against SMART and centroid weighting schemes. TOPSIS was not found to be more accurate, but was quite close in accuracy. Using first-order and second-order metrics were found to be quite good, but the infinite order (Chebyshev norm, \(L_\infty\)) was found to decline in accuracy.

MSC:
90B50 Management decision making, including multiple objectives
Software:
MADM
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Yoon, K., Systems selection by multiple attribute decision making, ()
[2] Hwang, C.L.; Yoon, K., Multiple attribute decision making: methods and applications, (1981), Springer-Verlag New York
[3] Lai, Y.-J.; Liu, T.-Y.; Hwang, C.-L., TOPSIS for MODM, European journal of operational research, 76, 3, 486-500, (1994) · Zbl 0810.90078
[4] Yoon, K.; Hwang, C.L., Multiple attribute decision making: an introduction, (1995), Sage New York
[5] Hwang, C.L.; Lai, Y.-J.; Liu, T.Y., A new approach for multiple objective decision making, Computers & operations research, 20, 889-899, (1993) · Zbl 0781.90058
[6] Yoon, K.P., A reconciliation among discrete compromise solutions, Journal of the operational research society, 38, 3, 277-286, (1987) · Zbl 0608.90054
[7] Zanakis, S.H.; Solomon, A.; Wishart, N.; Dublish, S., Multi-attribute decision making: A simulation comparison of select methods, European journal of operational research, 107, 3, 507-529, (1998) · Zbl 0943.90054
[8] Agrawal, V.P.; Kohli, V.; Gupta, S., Computer aided robot selection: the multiple attribute decision making approach, International journal of production research, 29, 8, 1629-1644, (1991)
[9] Agrawal, V.P.; Verma, A.; Agrawal, S., Computer-aided evaluation and selection of optimum grippers, International journal of production research, 30, 11, 2713-2732, (1992)
[10] Kim, G.; Park, C.; Yoon, K.P., Identifying investment opportunities for advanced manufacturing system with comparative-integrated performance measurement, International journal of production economics, 50, 23-33, (1997)
[11] Chau, O.L.; Parkan, C., Selection of a manufacturing process with multiple attributes: A case study, Journal of engineering technology management, 12, 219-237, (1995)
[12] Parkan, C.; Wu, M.L., On the equivalence of operational performance measurement and multiple attribute decision making, International journal of production research, 35, 11, 2963-2988, (1997) · Zbl 0942.90554
[13] Parkan, C.; Wu, M.L., Process selection with multiple objective and subjective attributes, Production planning P9 control, 9, 2, 189-200, (1998)
[14] Parkan, C.; Wu, M.-L., Decision-making and performance measurement models with applications to robot selection, Computers & industrial engineering, 36, 3, 503-523, (1999)
[15] Cha, Y.; Jung, M., Satisfaction assessment of multi-objective schedules using neural fuzzy methodology, International journal of production research, 41, 8, 1831-1849, (2003) · Zbl 1059.90081
[16] Chu, T.-Ch., Facility location selection using fuzzy TOPSIS under group decisions, International journal of uncertainty, fuzziness & knowledge-based systems, 10, 6, 687-701, (2002) · Zbl 1065.90085
[17] Deng, H.; Yeh, C.-H.; Willis, R.J., Inter-company comparison using modified TOPSIS with objective weights, Computers & operations research, 27, 10, 963-974, (2000) · Zbl 0970.90038
[18] Feng, C.-M.; Wang, R.-T., Considering the financial ratios on the performance evaluation of highway bus industry, Transport reviews, 21, 4, 449-467, (2001)
[19] Brans, J.P.; Vincke, P.; Mareschal, B., How to select and how to rank projects: the PROMETHEE method, European journal of operational research, 24, 228-238, (1986) · Zbl 0576.90056
[20] Roy, B., Clessement et choix en presence de criteres multiples, Riro, 8, 57-75, (1968)
[21] Saaty, T.L., A scaling method for priorities in hierarchical structures, Journal of mathematical psychology, 15, 3, 234-281, (1977) · Zbl 0372.62084
[22] Olson, D.L., Comparison of three multicriteria methods to predict known outcomes, European journal of operational research, 130, 576-587, (2001) · Zbl 0983.90031
[23] Edwards, W., How to use multiattribute utility measurement for social decisionmaking, IEEE transactions on systems, man, and cybernetics, SMC-7, 5, 326-340, (1977)
[24] Edwards, W.; Barron, F.H., SMARTS and SMARTER: improved simple methods for multiattribute utility measurement, Organizational behavior and human decision processes, 60, 306-325, (1994)
[25] Olson, D.L.; Dorai, V.K., Implementation of the centroid method of solymosi and dombi, European journal of operational research, 60, 1, 117-129, (1992) · Zbl 0825.90570
[26] Sprent, P., Applied nonparametric statistical methods, (1989), Chapman and Hall Thousand Oaks, CA · Zbl 0991.62027
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.