DecisionMind · multi-criteria decisions under uncertainty

What shall we decide today?

Upload a decision matrix whose cells carry uncertainty (fuzzy, interval, intuitionistic, neutrosophic and other data families) and rank the alternatives with the methods written for that family: 335 validated methods in all. The result arrives as an editable report with robustness checks built in.

Start an analysis How it works

From data to report in four steps

Bring your data

Drop a CSV or Excel matrix or start from a sample. The data family is recognised from the cells, or you declare it; alternatives, criteria and their directions are read for you.

Frame the decision

State the goal, check each criterion's direction and, when several people judge, add their matrices as a group decision.

Weight and choose methods

Take weights from the data, type your own or keep them equal, then pick a ranking method and compare up to 12 methods side by side.

Read and export the report

The report opens in an editor laid out like a Word page, with leave-one-out and rank-reversal checks included. Export to Word, Excel, HTML or PDF.

Built for decisions you can defend

Group decisions

Combine several decision makers' matrices where the data family supports it; the report states how they were combined.

Method comparison

Run several ranking methods on the same data and read how closely their rankings agree.

Robustness by default

Every result is re-run with each alternative and each criterion left out in turn, so you see whether the leader holds.

A report you can cite

Each method follows a published source; the report names it, records every setting and explains the result in plain language.

Variant works with data that carries uncertainty

Each cell holds an uncertain value: a fuzzy number, an interval, an intuitionistic, Pythagorean, neutrosophic, grey or hesitant value, and more. Data of plain (crisp) numbers is analysed in DecisionMind Crisp; the Academy explains the methods of both.