Trade Study Execution and Analysis

Designed a website to conduct and store trade studies using Vue.js as a front end framework for making dynamic pages and Spring Boot as back end framework for creating rest services. Created algorithms with Analytical Hierarchy Process and analyzed subsequently data to identify trends using Java and MatLab.

Analytical Hierarchy Process

The Analytic Hierarchy Process (AHP) was first created by Thomas Saaty in 1977. The model was designed to use pairwise comparisons, between both the options and the criteria used in the model, to create a model that could determine the optimal solution to a decision. The Ideal Analytic Hierarchy Process, a revised version of the Analytic Hierarchy Process, is what will be used in this model. While there are many different multi-criteria decision-making models that can be used, the Ideal Hierarchy Process is the least likely to give you an incorrect optimal solution.

Ideal Analytic Hierarchy Process will be used as basic algorithm in this model, and there are details of algorithm and pseudo. There is a paper to introduce using analytic hierarchy process for decision making as well.

Tools

Vue: the progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Netbeans IDE: implement the algorithm with Java.
MatLab: analysis the data and identify trends to generate a stacked bar scores.
MySQL & SQL: storing, manipulating and retrieving data in databases.

Evaluation

Define Trade: trade study name, program name, topic name, author
Define Parameters: numbers, names, types, preferences, comparisons
Define Options: numbers, names
Evaluate Options: receive raw score matrix
Compare and Select: determine solution and confidence factor, plot results, export a data file with results in database