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Essential Guide to Evaluation and Optimization Models: Resources & Algorithms

This curated list compiles recent articles on evaluation and optimization models, covering Data Envelopment Analysis, ANP, VIKOR, various grey analysis methods, competition ranking techniques, case studies, linear and integer programming, and a range of optimization algorithms with Python examples.

Model Perspective
Model Perspective
Model Perspective
Essential Guide to Evaluation and Optimization Models: Resources & Algorithms

1. Evaluation Models

1.1 Data Envelopment Analysis (DEA)

DEA (Part 1) – Introduction

DEA (Part 2) – Model Introduction

DEA (Part 3) – Mathematical Model

Output‑oriented DEA model

Input‑oriented DEA model

Input‑output slacks DEA model

DEA application case studies

University evaluation DEA case

DEA case analysis with Python code

1.2 Other Comprehensive Methods

ANP (Analytic Network Process) – Network analysis method

VIKOR model

Grey relational analysis

Grey comprehensive evaluation – case study

Grey comprehensive evaluation – principles

1.3 Competition Evaluation

Messe method for competition ranking

Kenya method

Markov method

1.4 Case Studies

Implementation process of sports curriculum learning evaluation

Determining weights for classroom teaching fairness indicators

Construction of evaluation indicators for ordinary university sports learning

Comparison of various weighting methods and 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)

Teaching‑learning optimization algorithm (Python)

Particle Swarm Optimization (PSO) for Rastrigin function

Genetic algorithm for Rastrigin function

Genetic algorithm using Geatpy library (Python)

pythonoperations researchmodel evaluationoptimization algorithmsDEA
Model Perspective
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Model Perspective

Insights, knowledge, and enjoyment from a mathematical modeling researcher and educator. Hosted by Haihua Wang, a modeling instructor and author of "Clever Use of Chat for Mathematical Modeling", "Modeling: The Mathematics of Thinking", "Mathematical Modeling Practice: A Hands‑On Guide to Competitions", and co‑author of "Mathematical Modeling: Teaching Design and Cases".

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