Analytic Hierarchy Process

A technique for organizing and analyzing complex multi-objective decisions

版本 3.0.0 (34.5 KB)
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2026/9/21

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Analytic Hierarchy Process (AHP) is a simple technique, developed by Thomas L. Saaty in the 1970s, for organizing and analyzing complex multi-objective decisions. It combines both quantitative and qualitative analysis elements and it finds application in group decision making. The philosophy of the technique is to decompose problem into a hierarchy of more easily understood sub-problems, each of which can be analyzed independently. Once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them to one another two at a time, with respect to their impact on an element above them in the hierarchy. The AHP converts these evaluations to numerical values that can be processed and compared over the entire range of the problem. A numerical weight is derived for each element of the hierarchy, allowing diverse and often incommensurable elements to be compared to one another in a rational and consistent way. In the final step of the process, numerical weights are calculated for each of the decision alternatives. These weights represent the alternatives' relative ability to achieve the goal.
The function facilitates the following:
• Simple AHP implementation
• Multiple decision makers
• Analytic Network Process (ANP): The generalization of the AHP, which incorporates dependences and feedbacks between decision criteria and options.
• Fuzzy AHP and ANP: This are special versions of the simple AHP and ANP, which find application in fuzzy environments, where the relative importance of the decision criteria and the alternatives is uncertain.
• Simulation: A Monte-Carlo simulation-based approach of AHP and ANP, which allows to compare distributions of weights and performs sensitivity analysis.
• Cost-Benefit analysis: The benefit (AHP weights) in relationship with the cost of the respective option.
• Optimization: In case of a resource allocation problem, the function estimates the optimal feasible combination of alternatives subject to the resources’ constraints.
• Prediction combination: In case this is a forecasting combination problem, the function generates a weighted average forecast, using the combination weights and the individual forecasts as inputs.
The package includes AHP Decision Studio, a graphical interface for users who prefer to work without writing code.
The interface guides users through defining alternatives and criteria, assessing criterion importance, entering pairwise comparisons or numerical performance values, and reviewing the results. It includes:
• Dropdown-based pairwise comparisons and numerical criteria where higher or lower values are preferred.
• Ranking charts, results tables, and criterion-level priorities.
• Sensitivity analysis with mean weights and percentile ranges.
• Optional fuzzy approximation, network feedback, benefit–cost analysis, and budget-constrained selection.
• Project saving and reopening, CSV export, and chart export as PNG.
• A ready-to-run example and a user guide.
To launch the interface, open START_HERE.m in MATLAB and click Run. No code editing is required. The interface supports a single decision maker and one cost resource.
The ahp.m function remains fully usable independently of the interface. Users can call it directly from the MATLAB Command Window or their own scripts, including for multiple decision makers, multiple resource constraints, and forecast combination. Place ahp.m in your working folder or on the MATLAB path.
The graphical interface requires MATLAB R2020b or newer. Budget-constrained optimization requires Optimization Toolbox.

引用格式

Apostolos Panagiotopoulos (2026). Analytic Hierarchy Process (https://ww2.mathworks.cn/matlabcentral/fileexchange/79643-analytic-hierarchy-process), MATLAB Central File Exchange. 检索时间: .

一般信息

MATLAB 版本兼容性

  • 与 R2020a 及更高版本兼容

平台兼容性

  • Windows
  • macOS
  • Linux
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版本 已发布 发行说明
3.0.0

Added AHP Decision Studio, a guided graphical interface with editable comparisons, numerical performance inputs, ranking charts, sensitivity ranges, project saving/loading, and CSV/PNG export. Includes an example and a user guide. The ahp.m function

2.0.8

Small update in output print
2.0.7

small correction
2.0.6

Updating the lag function
2.0.5

Small correction
2.0.4

Another small correction
2.0.3

Small correction
2.0.2

Small correction in fuzzy model
2.0.1

Logical correction in the example
2.0.0

A new version with greater emphasis on simulation
1.1.5

Correction in the simulation function
1.1.4

Correction of two small bugs
1.1.3

Addition of Fuzzy AHP and ANP and correction of the comments
1.1.2

Addition of Fuzzy AHP and ANP options
1.1.1

The function now facilitates the option to use purely quantitative criteria, avoiding the pairwise comparison, and allows to use more than one cost measures.

1.1.0

Correction of the notes in the example
1.0.9

correction to the function code
1.0.8

More extended example and small update on the function code
1.0.7

Addition of an example code
1.0.6

Addition of a Cost-Benefit analysis option
1.0.5

Updated user's guide in the code and description
1.0.4

Updated user's guide in the code
1.0.3

Change in the description and the notes
1.0.2

Description update. Code remains the unchanged.
1.0.0