A decision support system for techno-economic evaluation of indoor lighting systems with LED luminaires

  • Evangelos-Nikolaos D. MadiasEmail author
  • Lambros T. Doulos
  • Panagiotis A. Kontaxis
  • Frangiskos V. Topalis
Original paper


The necessity for energy saving in lighting leads to installation of new energy efficient light sources, especially LED luminaires. Although solid state lighting is considered the dominant lighting technology for the future there exist no concrete methods to evaluate LED luminaires and decide the optimal one for each lighting application. Multicriteria decision methods are utilized in various decision problems so as to evaluate alternatives through complex and conflicting criteria. This paper introduces a decision support system for a complete techno-economic evaluation of LED luminaires through multicriteria analysis. Seven criteria are proposed so as to assess the technical and economic characteristics of LED luminaires and ensure their compliance with European Norms regarding office lighting. Laboratory measurements and lighting calculations in 8 indoor types of LED luminaires are performed so as to define their technical characteristics and evaluate their performance concerning the lighting of an office. Finally, the PROMETHEE II multicriteria method is applied, which ranks the 8 types of luminaires and determines the optimal one. The proposed decision support system can be applied to any type of luminaire and can be used by professionals who want to evaluate different luminaire suppliers and determine the optimal luminaire tender for the lighting of any indoor space.


Decision support systems LED luminaires Evaluation Multicriteria PROMETHEE II 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Adam GK, Kontaxis PA, Doulos LT, Madias END, Bouroussis CA, Topalis FV (2019) Embedded microcontroller with a CCD camera as a digital lighting control system. Electronics 8(1):33. CrossRefGoogle Scholar
  2. Ahn BL, Jang CY, Leigh SB, Yoo S, Jeong H (2014) Effect of LED lighting on the cooling and heating loads in office buildings. Appl Energy 113:1484–1489. CrossRefGoogle Scholar
  3. Al-Alawi BM, Coker AD (2018) Multi-criteria decision support system with negotiation process for vehicle technology selection. Energy 157:278–296. CrossRefGoogle Scholar
  4. Andreopoulou Z, Kokkinakis A, Koutroumanidis T (2009) Assessment and optimization of e-commerce websites of fish culture sector. Oper Res Int J 92:93–309. Google Scholar
  5. Andreopoulou Z, Koliouska C, Lemonakis C, Zopounidis K (2015) National Forest Parks development through Internet technologies for economic perspectives. Oper Res Int J 15:395–421. CrossRefGoogle Scholar
  6. Andreopoulou Z, Koliouska C, Galariotis E, Zopounidis K (2018) Renewable energy sources: using PROMETHEE II for ranking websites to support market opportunities. Technol Forecast Soc Chang 131:31–37. CrossRefGoogle Scholar
  7. Ballis A, Mavrotas G (2007) Freight village design using the multicriteria method PROMETHEE. Oper Res Int J 7:213–231. CrossRefGoogle Scholar
  8. Behzadian M, Albadvi A, Aghdasi M (2010) PROMETHEE: a comprehensive literature review on methodologies and applications. Eur J Oper Res 200:198–215. CrossRefGoogle Scholar
  9. Blanco AM, Parra EE (September 2010). Effects of High Penetration of CFLs and LEDs on the Distribution Networks. In: Proceedings of 14th international conference on harmonics and quality of power - ICHQP 2010, IEEE, Bergamo, Italy.
  10. Bouyssou D (1990) Building criteria: a prerequisite for MCDA. In: Bana e Costa CA (ed) Readings in multiple criteria decision-aid. Springer, Berlin, pp 58–80. CrossRefGoogle Scholar
  11. Boyce PR (2014) Human factors in lighting, 3rd edn. CRC Press, FloridaCrossRefGoogle Scholar
  12. Brans JP, Mareschal B, Vincke Ph (1986) How to select and how to rank projects: the PROMETHEE method. Eur J Oper Res 24:228–238. CrossRefGoogle Scholar
  13. Bunjongjit S, Ngaopitakkul A, Leelajindakrairerk M (2017). Analysis of harmonics in indoor lighting system with LED and fluorescent luminaire. In: 2017 IEEE 3rd International future energy electronics conference and ECCE Asia (IFEEC 2017 - ECCE Asia). IEEE, Kaohsiung, Taiwan.
  14. Chelmis E, Niklis D, Baourakis G, Zopounidis C (2017) Multiciteria evaluation of football clubs: the Greek Superleague. Oper Res. Google Scholar
  15. Coban A, Ertis IF, Cavdaroglu NA (2018) Municipal solid waste management via multi-criteria decision making methods: a case study in Istanbul, Turkey. J Clean Prod 180:159–167. CrossRefGoogle Scholar
  16. De Boni A, Roma R, Palmisano GO (2018) Fishery policy in the European Union: a multiple criteria approach for assessing sustainable management of Coastal Development Plans in Southern Italy. Ocean Coast Manag 163:11–21. CrossRefGoogle Scholar
  17. Dirutigliano D, Delmastro C, Moghadam ST (2018) A multi-criteria application to select energy retrofit measures at the building and district scale. Therm Sci Eng Progress 6:457–464. CrossRefGoogle Scholar
  18. Doukas H (2012) Linguistic multicriteria decision making for energy systems: building the “RE2S” framework. Wiley Interdiscip Rev Energy Environ 2(5):571–585. CrossRefGoogle Scholar
  19. Doukas H, Patlitzianas KD, Psarras J (2006) Supporting sustainable electricity technologies in Greece using MCDM. Resour Policy 31:129–136. CrossRefGoogle Scholar
  20. Doulos L, Tsangrassoulis A, Topalis FV (2014) Multi-criteria decision analysis to select the optimum position and proper field of view of a photosensor. Energy Convers Manag 86:1069–1077. CrossRefGoogle Scholar
  21. Doulos L, Tsangrassoulis A, Kontaxis PA, Kontadakis A, Topalis FV (2017) Harvesting daylight with LED or T5 fluorescent lamps? The role of dimming. Energy Build 140:336–347. CrossRefGoogle Scholar
  22. Doumpos M, Zopounidis C (2010) A multicriteria decision support system for bank rating. Decis Support Syst 50:55–56. CrossRefGoogle Scholar
  23. European Norm, EN 12464-1 (2011) Light and lighting—lighting of work places? Part 1: Indoor work places, European Committee for StandardizationGoogle Scholar
  24. European Norm, EN 13032-1 (2004) Light and lighting: measurement and presentation of photometric data of lamps and luminaires—Part 1: measurement and file format, European Committee for StandardizationGoogle Scholar
  25. Fan J, Yung KC, Pecht M (2015) Predicting long-term lumen maintenance life of LED light sources using a particle filter-based prognostic approach. Expert Syst Appl 42:2411–2420. CrossRefGoogle Scholar
  26. Govindan K, Kadziński M, Sivakumar R (2017) Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega 71:129–145. CrossRefGoogle Scholar
  27. Hellenic Ministry of Environment, Energy and Climate (2017). Greek Regulation for the Energy Efficiency of BuildingsGoogle Scholar
  28. Illuminating Engineering Society of North America (2008). Electrical and Photometric Measurements of Solid-State Lighting Products, Publication IES-LM-79-08, New York, NYGoogle Scholar
  29. International Committee on Illumination (1987). Measurement of Absolute Luminous Intensity Distributions, Technical Report N. 70, CIE Central Bureau, Vienna, AustriaGoogle Scholar
  30. International Committee on Illumination (1996). The Photometry and Goniophotometry of Luminaires, Technical Report N. 121, CIE Central Bureau, Vienna, AustriaGoogle Scholar
  31. International Committee on Illumination (2015) Test method for LED Lamps, LED Luminaires and LED modules, standard S 025/E:2015. CIE Central Bureau, ViennaGoogle Scholar
  32. Islam MS, Dangol R, Hyvärinen M, Bhusal P, Puolakka M, Halonen L (2015) User acceptance studies for LED office lighting: lamp spectrum, spatial brightness and illuminance. Light Res Technol. 47(1):54–79CrossRefGoogle Scholar
  33. Kazana H, Ertok M, Ciftci C (2015) Application of a hybrid method in the financial analysis of firm performance. Proc Soc Behav Sci 195:403–412. CrossRefGoogle Scholar
  34. Kontaxis PA, Madias END, Zevgolis D, Topalis FV (2013). Evaluation of image sensors for lighting control applications. In: 12th European lighting conference, Lux Europa 2013, Krakow, PolandGoogle Scholar
  35. Koutroumanidis T, Papathanasiou J, Manos B (2002) A multicriteria analysis of productivity of agricultural regions of Greece. Oper Res Int J 2:339–346. CrossRefGoogle Scholar
  36. Lafont U, van Zeijl H, van der Zwaag S (2012) Increasing the reliability of solid state lighting systems via self-healing approaches: a review. Microelectron Reliab 52:71–89. CrossRefGoogle Scholar
  37. Lowry G (2016) Energy saving claims for lighting controls in commercial buildings. Energy Build 133:489–497. CrossRefGoogle Scholar
  38. Madias END, Kontaxis PA, Topalis FV (2016) Application of multi-objective generic algorithms to interior lighting optimization. Energy Build 125:66–74. CrossRefGoogle Scholar
  39. McKinsey Company (2011) Lighting the way: perspectives on the Global Lighting Market. McKinsey, New YorkGoogle Scholar
  40. Papapostolou A, Karakosta C, Doukas H (2017) Analysis of policy scenarios for achieving renewable energy sources targets: A fuzzy TOPSIS approach. Energy Environ 28:88–109. CrossRefGoogle Scholar
  41. Pendaraki K, Zopounidis C (2003) Evaluation of equity mutual funds’ performance using a multicriteria methodology. Oper Res Int J 3:69–90.CrossRefGoogle Scholar
  42. Peruffo A, Pandharipande A, Caicedo D, Schenato L (2015) Lighting control with distributed wireless sensing and actuation for daylight and occupancy adaptation. Energy Build 97:13–20. CrossRefGoogle Scholar
  43. Principi P, Fioretti R (2014) A comparative life cycle assessment of luminaires for general lighting for the office e compact fluorescent (CFL) vs Light Emitting Diode (LED): a case study. J Clean Prod 38:96–107. CrossRefGoogle Scholar
  44. RELUX Documentation. Accessed 4 Dec 2018
  45. Sayadi MK, Heydari M, Shahanaghi K (2009) Extension of VIKOR method for decision making problem with interval numbers. Appl Math Model 33:2257–2262. CrossRefGoogle Scholar
  46. Singh A, Gupta A, Mehra A (2017) Energy planning problems with interval-valued 2-tuple linguistic information. Oper Res Int Journal 17:821–848. CrossRefGoogle Scholar
  47. Tan PS, Lee SSG, Goh AES (2012) Multi-criteria decision techniques for context-aware B2B collaboration in supply chains. Decis Support Syst 72:779–789. CrossRefGoogle Scholar
  48. The Society of Light and Lighting (2012) SLL Code on Lighting. The Chartered Institution of Building Services Engineers, LondonGoogle Scholar
  49. Van Bommel WJM, Van den Beld GJ (2004) Lighting for work: a review of visual and biological effects. Light Res Technol 36:255–269.CrossRefGoogle Scholar
  50. Vasić G (2018) Application of multi criteria analysis in the design of energy policy: space and water heating in households—City Novi Sad, Serbia. Energy Policy 113:410–419. CrossRefGoogle Scholar
  51. Visual PROMETHEE 1.4, Academic edition documentation. Accessed 4 Dec 2018
  52. Wiecek M, Ehrgott M, Fadel G, Figueira J (2008) Multiple criteria decision making for engineering. Omega 36:337–504. CrossRefGoogle Scholar
  53. Xidonas P, Flamos A, Koussouris S, Askounis D, Psarras I (2007) On the appraisal of consumer credit banking products within the asset quality frame: a multiple criteria application. Oper Res Int Journal 7:255–283. CrossRefGoogle Scholar
  54. Yan C, Rousse D, Glaus M (2019) Multi-criteria decision analysis ranking alternative heating systems for remote communities in Nunavik. J Clean Prod 208:1488–1497. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Lighting Laboratory, School of Electrical and Computer EngineeringNational Technical University of AthensZografouGreece
  2. 2.School of Applied Arts, Lighting DesignHellenic Open UniversityPatrasGreece
  3. 3.Department of Electrical and Electronics Engineering, Faculty of EngineeringUniversity of West AtticaEgaleoGreece

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