A Curated Guide to Evaluation and Optimization Models for Researchers

1. Evaluation Models

1.1 Data Envelopment Analysis (DEA)

Introduction and basic concepts

Output‑oriented model

Input‑oriented model

Input‑output slack model

DEA application cases (e.g., university evaluation)

Python case study with code

1.2 Other Comprehensive Methods

Network Analysis ANP

VIKOR model

Grey relational analysis and its applications

Comprehensive grey evaluation method

1.3 Competition Evaluation

Messe method for ranking

Kenya method

Markov method

1.4 Case Studies

Physical‑education course evaluation process

Determining weights for classroom teaching fairness

Construction of evaluation indicators for university sports learning

Comparison of weighting methods with empirical analysis

2. Optimization Models

2.1 Linear and Integer Programming

Human‑resource planning

Edible‑oil refining problem

Signal‑tower coverage problem

Enumeration method for solving linear programming

2.2 Optimization Algorithms

Butterfly algorithm

Bee‑colony algorithm

Seagull algorithm (Python)

Particle Swarm Optimization (PSO) for Rastrigin function

Genetic algorithm for Rastrigin function

Geatpy library for genetic algorithm in Python