flutter_decision_making 2.0.0

Flutter package for multi-criteria decision-making using AHP, SAW, and TOPSIS algorithms.

2.0.0

Breaking changes

• Isolate execution is now opt-in. The automatic isolate threshold (>80 alternatives / >25 criteria) was removed. All calculation methods accept useIsolate (default false). In profile-mode benchmarks on Apple Silicon, the main-thread path was roughly 8–50x faster than the isolate path for SAW and TOPSIS up to 2000x50 (see README).
• Isolate internals are no longer exported from package:flutter_decision_making/flutter_decision_making.dart (DecisionIsolateMain, isolate message and worker files). Migration: pass useIsolate: true to the public API; if you need the manager itself, import package:flutter_decision_making/core/isolate/decision_isolate_main.dart.

Added

• New pure Dart package decision_making_core (packages/decision_making_core) with synchronous SAW, TOPSIS and AHP calculators. The Flutter package delegates its calculations to it.
• Entity types from the core are exported selectively from the main barrel.
• TOPSIS, TopsisRawMatrix and related types are now exported from the main barrel.
• Detailed self-explaining SAW results (SawDetailedResult): Added SawCalculator.calculateDetailed and SAW.getSawDetailedResult returning all intermediate calculation steps: input matrix, cell-normalized matrix (r_ij), normalized weights (w_j), weighted cell matrix (v_ij), and final scores/ranks with JSON serialization support (toJson()).
• Detailed self-explaining TOPSIS results (TopsisDetailedResult): Added TopsisCalculator.calculateDetailed and TOPSIS.getTopsisDetailedResult returning all intermediate calculation steps: input matrix, Euclidean-normalized matrix (r_ij), normalized weights (w_j), weighted cell matrix (v_ij), positive/negative ideal solutions (A+, A-), separation distances (D+, D-), and final relative closeness scores/ranks with JSON serialization support (toJson()).
• Detailed self-explaining AHP results (AhpDetailedResult, AhpMatrixEvaluation): Added AhpCalculator.calculateDetailed and AHP.getAhpDetailedResult returning all intermediate comparison matrices, normalized matrices, weights (w_j), consistency metrics (lambda_max, CI, RI, CR), per-criteria local priority scores, weighted scores, and final synthesized scores with JSON serialization support (toJson()).
• Weight sensitivity analysis & rank reversal detection (SAW & TOPSIS): Added SawCalculator.analyzeSensitivity, TopsisCalculator.analyzeSensitivity, SAW.analyzeSensitivity, and TOPSIS.analyzeSensitivity returning SensitivityAnalysisResult with systematic +/- delta perturbations, pairwise ranking change detection, alternative removal rank reversal tests, and JSON serialization support (toJson()).
• Exported sensitivity entities: AlternativePair, RankReversalCase, SensitivityAnalysisResult, SensitivityDirection, and WeightSensitivityCase.

Fixed

• TOPSIS ranking was wrong in 1.2.0 for datasets above 80 alternatives or 25 criteria, because the isolate worker called the SAW normalization instead of the Euclidean one.
• Removed a dead TOPSIS isolate command (normalizeMatrix).

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1.2.0

Updated

• make shared function to generate matrix for SAW and TOPSIS
• added algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)

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1.1.2

Updated

• add support me on ko-fi, saweria to readme

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1.1.1

Updated

• adding Simple Additive Weighting (SAW) algorithm
• main isolate manager, make to multi-command isolate
• minimum flutter version
• minor update AHP

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1.0.6

Updated

• update README.md
• Refactored AHP feature for improved maintainability and performance
• On mobile and desktop platforms, replaced compute with Isolate.spawn for heavy processing tasks:
  • generateResultPairwiseMatrixCriteria
  • generateResultPairwiseMatrixAlternative
  • calculateEigenVectorCriteria
  • calculateEigenVectorAlternative
  • checkConsistencyRatio
  • ahpFinalScore

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1.0.5

Changed

• Refactor feature AHP.

Added

• Added isolate-based heavy processing for:
  • generatePairwiseAlternativeInput
  • generateResultPairwiseMatrixCriteria
  • generateResultPairwiseMatrixAlternative
  • calculateEigenVectorCriteria
  • calculateEigenVectorAlternative
  • checkConsistencyRatio

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1.0.4

• updated README with development note about upcoming support for SAW, TOPSIS, and other algorithms.
• Improved package description in pubspec.yaml to reflect ongoing development and future feature additions.

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1.0.3

• update preference value: only return integer
• update README.md
• feature to reset all internal data and results to initial state

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1.0.2

update docs

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1.0.1

chore:

• Provide documentation
• Pass static analysis
• update README.md

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1.0.0

• Flutter Decision Making with AHP algorithm initial release.