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Encyclopedia of Multi-Attribute Decision Making (MADM)

  • 1st Edition - August 1, 2026
  • Latest edition
  • Editors: Gholamreza Haseli, Muhammet Deveci, Mostafa Hajiaghaei-Keshteli
  • Language: English

Encyclopedia of Multi-Attribute Decision Making (MADM) presents current methods in MADM in a simple way, including Sections on Weighting Methods, Extensions for the MADM Method… Read more

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Description

Encyclopedia of Multi-Attribute Decision Making (MADM) presents current methods in MADM in a simple way, including Sections on Weighting Methods, Extensions for the MADM Methods, Ranking Methods, and Outranking Methods. Each method chapter presents two numerical examples for each method, one simple example with less than six criteria and six alternatives, and one complex example with six or more criteria and six or more alternatives. In addition, most chapters are written by the original developers of the method, ensuring insight into and practical application of MADM. The book is also filled with over 200 full-color figures that illustrate methods and applications.

The book, in one volume, demystifies the complex world of MADM, blending theoretical concepts with hands-on practices and case studies. It bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of MADM.

Key features

  • Includes chapters on all the current Multi-Attribute Decision Making methods, including Sections on Weighting Methods, Extensions for the MADM Methods, Ranking Methods, and Outranking Methods
  • Presents a consistent structure, enabling easier learning of methods
  • Provides two numerical examples for each method, one simple example with less than six criteria and six alternatives, and one complex example with six or more criteria and six or more alternatives
  • Includes comprehensive coverage of balanced theory and practice, thus ensuring a strong theoretical foundation paired with actionable insights for real-world applications

Readership

Researchers and graduate students in computer science, AI, machine learning, deep learning; professional software developers and data scientists, industrial and systems engineers

Table of contents

Section 1: Weighting methods

1. AHP: Analytic Hierarchy Process for Multi-Attribute Decision-Making

2. ANP: Analytic Network Process for Multi-Attribute Decision-Making

3. DEMATEL: Decision-Making Trial and Evaluation Laboratory for Multi-Attribute Decision-Making

4. DANP: DEMATEL-based ANP for Multi-Attribute Decision-Making

5. WINGS: weighted influence nonlinear gauge system for Multi-Attribute Decision-Making

6. CRITIC: CRiteria Importance Through Intercriteria Correlation for Multi-Attribute Decision-Making

7. REGIME: Ranks and Evaluation by Guide Indices and Matrices for Evaluation for Multi-Attribute Decision-Making

8. PAPRIKA: Potentially All Pairwise Rankings of all possible Alternatives for Multi-Attribute Decision-Making

9. QFD: Quality Function Deployment for Multi-Attribute Decision-Making

10. SMART: Simple Multi-Attribute Rating Technique for Multi-Attribute Decision-Making

11. COMET: Characteristic Objects METhod for Multi-Attribute Decision-Making

12. DIBR: Defining Interrelationships Between Ranked for Multi-Attribute Decision-Making

13. SWARA: Stepwise Weight Assessment Ratio Analysis for Multi-Attribute Decision-Making

14. BWM: Best-Worst Method for Multi-Attribute Decision-Making

15. Stratified BWM: Stratified Best-Worst Method for Multi-Attribute Decision-Making

16. Bayesian BWM: Bayesian Best-Worst Method for Multi-Attribute Decision-Making

17. Nonadditive BWM: Nonadditive Best-Worst Method for Multi-Attribute Decision-Making

18. BWT: Best Worst Tradeoff for Multi-Attribute Decision-Making

19. IDOCRIW: Integrated Determination of Objective CRIteria Weights for Multi-Attribute Decision-Making

20. PIPRECIA: PIvot Pair-wise RElative Criteria Importance Assessment method for Multi-Attribute Decision-Making

21. FUCOM: Full consistency method for Multi-Attribute Decision-Making

22. LBWA: Level Based Weight Assessment for Multi-Attribute Decision-Making

23. OPA: Ordinal priority approach for Multi-Attribute Decision-Making

24. RAFSI: Ranking of Alternatives Through Functional Mapping of Criterion Sub-Intervals into a Single Interval for Multi-Attribute Decision-Making

25. ITARA: indifference threshold-based attribute ratio analysis for Multi-Attribute Decision-Making

26. BCM: Base-Criterion Method for Multi-Attribute Decision-Making

27. Stratified BCM: Stratified Base-Criterion Method for Multi-Attribute Decision-Making

28. BCT: Base Criterion Tradeoff for Multi-Attribute Decision-Making

29. Nonadditive BCM: Nonadditive Base-Criterion Method for Multi-Attribute Decision-Making

30. BRAW: block-wise rating the attribute weights for Multi-Attribute Decision-Making

31. CIMAS: Criteria Importance Assessment for Multi-Attribute Decision-Making

32. MEREC: Method Based on the Removal Effects of Criteria for Multi-Attribute Decision-Making

33. LMAW: Logarithm Methodology of Additive Weights for Multi-Attribute Decision-Making

34. IROC: Improved Rank Order Centroid for Multi-Attribute Decision-Making

35. SWM: Surrogate Weighting Method for Multi-Attribute Decision-Making

36. LOPCOW: LOgarithmic Percentage Change-driven Objective Weighting for Multi-Attribute Decision-Making

37. WENSLO: Weights by ENvelope and SLOpe for Multi-Attribute Decision-Making

38. COBRAC: COmparisons Between RAnked Criteria for Multi-Attribute Decision-Making

39. SiWeC: Simple Weight Calculation for Multi-Attribute Decision-Making

Section 2: Extensions for the MADM methods

40. Parsimonious: A Concept for Multi-Attribute Decision-Making

41. K-mean: Algorithm for Multi-Attribute Decision-Making

42. OWA: Ordered Weighted Averaging for Multi-Attribute Decision-Making

43. FCM: Fuzzy Cognitive Maps for Multi-Attribute Decision-Making

Section 3: Ranking methods

44. LINMAP: Linear Programming Technique for Multidimensional Analysis of Preference for Multi-Attribute Decision Making

45. TOPSIS: Technique for Order Preference by Similarity to Ideal Solution for Multi-Attribute Decision-Making

46. VIKOR: VlseKriterijumska Optimizacija I Kompromisno Resenje for Multi-Attribute Decision-Making

47. MOORA: Multi-Objective Optimization on the basis of Ratio Analysis for Multi-Attribute Decision-Making

48. MULTIMOORA: Multi‐Objective Optimization by Ratio Analysis plus Full Multiplicative Form for Multi-Attribute Decision-Making

49. SAW: Simple Additive Weighting for Multi-Attribute Decision-Making

50. MAUT: Multi Attribute Utility Method for Multi-Attribute Decision-Making

51. MPSI: Modified Preference selection index for Multi-Attribute Decision-Making

52. OCRA: Operational Competitiveness Ratings Analysis for Multi-Attribute Decision-Making

53. EATWIOS: Efficiency Analysis Technique with Input and Output Satisficing for Multi-Attribute Decision-Making

54. ARAS: Additive Ratio Assessment for Multi-Attribute Decision-Making

55. TODIM: TOmada de Decisão Interativa Multicriterio method for Multi-Attribute Decision-Making

56. COPRAS: COmplex PRoportional Assessment for Multi-Attribute Decision-Making

57. EDAS: Evaluation Based on Distance from Average Solution for Multi-Attribute Decision-Making

58. CODAS: COmbinative Distance-Based ASsessment for Multi-Attribute Decision-Making

59. MAIRCA: Multi-Atributive Ideal-Real Comparative Analysis for Multi-Attribute Decision-Making

60. MACBETH: Measuring Attractiveness by a Categorical Based Evaluation Technique for Multi-Attribute Decision-Making

61. WSM & WPM: Weighted Sum Model and Weighted Product Model for Multi-Attribute Decision-Making

62. WASPAS: Weighted Aggregated Sum Product Assessment for Multi-Attribute Decision-Making

63. MABAC: Multi-Attributive Border Approximation area Comparison for Multi-Attribute Decision-Making

64. SECA: Simultaneous Evaluation of Criteria and Alternatives for Multi-Attribute Decision-Making

65. TAOV: Total Area based on Orthogonal Vectors for Multi Attribute Decision-Making

66. CoCoSo: Combined Compromise Solution for Multi-Attribute Decision-Making

67. CoCoFISo: Combined Compromise for Ideal Solution for Multi-Attribute Decision-Making

68. WISP: Simple Weighted Sum Product for Ideal Solution for Multi-Attribute Decision-Making

69. SD-MCRAT: Standard Deviation Multiple Criteria Ranking by Alternative Trace for Multi-Attribute Decision-Making

70. MACONT: Mixed Aggregation by Comprehensive Normalization Technique for Multi-Attribute Decision-Making

71. OPTBIAS: Ordering Preference Targeting at Bi-Ideal Average Solutions for Multi-Attribute Decision-Making

72. MARCOS: Measurement Alternatives and Ranking according to Compromise Solution for Multi-Attribute Decision-Making

73. DNMA: Double Normalization-based Multi-Aggregation for Multi-Attribute Decision-Making

74. TRUST: A mulTi-noRmalization mUlti-distance aSsessmenT for Multi-Attribute Decision-Making

75. AROMAN: Alternative Ranking Order Method Accounting for two-step Normalization for Multi-Attribute Decision-Making

76. CRADIS: Compromise Ranking of Alternatives from Distance to Ideal Solution for Multi-Attribute Decision-Making

77. ADAM: Axial-Distance-Based Aggregated Measurement for Multi-Attribute Decision-Making

78. OPLO-POCOD: OPportunity LOsses-based POlar COordinate Distance for Multi-Attribute Decision-Making

79. ARLON: Alternative Ranking using two-step LOgarithmic Normalization for Multi-Attribute Decision-Making

80. ARWEN: Alternatives Ranking With Elected Nominee for Multi-Attribute Decision-Making

81. RAM: Root Assessment Method for Multi-Attribute Decision-Making

82. RANCOM: RANking COMparison for Multi-Attribute Decision-Making

83. RAWEC: Ranking of Alternatives with WEights of Criterion for Multi-Attribute Decision-Making

84. ERUNS: Evaluation based on Relative Utility and Nonlinear Standardization for Multi-Attribute Decision-Making

85. FUCA: Faire Un Choix Adéquat for Multi-Attribute Decision-Making

86. COBRA: COmprehensive Distance Based RAnking for Multi-Attribute Decision-Making

87. ALWAS: Aczel-Alsina Weighted Assessment for Multi-Attribute Decision-Making

88. RADAR: RAnking based on Distance And Range for Multi-Attribute Decision-Making

89. OPARA: Objective Pairwise Adjusted Ratio Analysis for Multi-Attribute Decision-Making

90. ARTASI: Alternative ranking technique based on adaptive standardized intervals for Multi-Attribute Decision-Making

91. RBNAR: Reference based Normalization Alternative Ranking for Multi-Attribute Decision-Making

92. CARD: Comprehensive Approach based on Relative Difference for Multi-Attribute Decision-Making

Section 4: Outranking methods

93. ELECTRE: ELimination and Choice Expressing REality for Multi-Attribute Decision-Making

94. ELECTRE II: Extension of the ELimination and Choice Expressing REality for Multi-Attribute Decision-Making

95. ELECTRE III: Extension of the ELimination and Choice Expressing REality for Multi-Attribute Decision-Making

96. ELECTRE TRI: ELimination and Choice Expressing REality for Multi-Attribute Decision-Making

97. PROMETHEE: Preference Ranking Organization METhod for Enrichment Evaluation for Multi-Attribute Decision-Making

98. PROMETHEE II: Extension of the Preference Ranking Organization METhod for Enrichment Evaluation for Multi-Attribute Decision-Making

99. ORESTE: Organization Rangement Et Synthese De Ronnees Relationnelles for Multi-Attribute Decision-Making

100. GLDS: Gained and Lost Dominance Score for Multi-Attribute Decision-Making

Product details

  • Edition: 1
  • Latest edition
  • Published: August 1, 2026
  • Language: English

About the editors

GH

Gholamreza Haseli

Gholamreza Haseli is currently a Research Assistant at University College Dublin, Ireland. Concurrently, he is a Ph.D. Candidate in Industrial Engineering at Tecnologico de Monterrey, Mexico. Recently, he introduced the Base-Criterion Method (BCM) and the HECON methods for multi-attribute decision-making. Gholamreza Haseli serves as a reliable group decision-making framework designer for analysis in the VOTE-TRA Project, funded by the Science Foundation Ireland through the Digital Voting Hub for Sustainable Urban Transport System (22/NCF/DR/11309). His research interests encompass decision science, fuzzy sets, fuzzy numbers, multi-criteria decision-making, waste management, and transportation.
Affiliations and expertise
School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico

MD

Muhammet Deveci

Dr. Muhammet Deveci is an Associate Professor at the Department of Industrial Engineering in the Turkish Naval Academy, National Defense University, Istanbul, Turkey, and he is Honorary Senior Research Fellow with the Bartlett School of Sustainable Construction, University College London, UK. Dr. Deveci is also a Visiting Professor at Royal School of Mines in the Imperial College London, London, UK. He worked as a Visiting Researcher and Postdoctoral Researcher, in 2014-2015 and 2018–2019, respectively, with the School of Computer Science, University of Nottingham, Nottingham, U.K. Dr Deveci is an outstanding researcher and has published over 240 papers in journals, as well as more than 25 contributions in International Conferences related to his areas. Dr. Deveci received the 100th-anniversary award for his worldwide scientific achievements from the Scientific and Technological Research Council of Turkey (TUBITAK).

Dr Deveci has also been engaged with the wider community providing academic service through chairing/organising conferences, streams, tutorials, reviewing papers, and acting as Editorial Board Member of journals including IEEE Transactions on Intelligent Vehicles (T-IV), IEEE Transactions on Emerging Topics in Computational Intelligence, Information Sciences, Applied Soft Computing, Engineering Applications of Artificial Intelligence, and Artificial Intelligence Review.

Dr Deveci is an internationally recognized scientist in intelligent decision support systems underpinned by computational intelligence, particularly uncertainty handling, fuzzy systems, combinatorial optimization, and multicriteria decision making. His research and development activities are multidisciplinary and lie at the interface of operational research, computer science and artificial intelligence. He has been tackling challenging real-world problems without stripping off their complexities, including climate change, renewable energy, sustainable transport, and urban mobility.

Affiliations and expertise
Department of Industrial Engineering, National Defense University, Istanbul, Turkey

MH

Mostafa Hajiaghaei-Keshteli

Prof. Mostafa Hajiaghaei-Keshteli is an Associate Professor at the Department of Industrial Engineering, Tecnológico de Monterrey, which is one of the most prestigious universities for industry and supply chain in Mexico. He is also a Co-founder and Senior Researcher at the Center of Sustainable Smart Logistics (CLIS), established in 2022, to offer sustainable logistics solutions to the public and private sector in Mexico and North America. He has developed famous metaheuristic algorithms, including algorithms such as Keshtel Alg., Red Deer Alg., Tree Growth Alg., and the Social Engineering Optimizer. He is also an editorial member in some top Q1 journals at Elsevier, such as Applied Soft Computing (ASOC), Engineering Applications of Artificial Intelligence (EAAI), and Expert Systems with Applications (ESWA). He has a solid industrial background, both in managerial and consulting sectors, in different industries such as agriculture, food, automotive, transportation, and engine industries.

Affiliations and expertise
Technology Institute of Monterrey, Puebla, Mexico