Discrete Optimization Data Science Heuristic & Metaheuristic
Ditulis pada: November 19, 2019
Free Coupon Discount - Discrete Optimization Data Science Heuristic & Metaheuristic, Discrete Optimization in Data Science: Heuristic and Metaheuristic Methods
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What you'll learn
What is optimization
- Some real-life situations where we need to optimize an objective
- The mathematical formalism of optimization
- How discrete optimization (Combinatorics) differs from continuous optimization
- Different approaches to solve a Combinatorics problem, including— The simplest, perfect but slow ‘Brute Force’ method. One of the fastest and practicable ‘Greedy’ heuristic.A look-ahead mechanism to refine the greedy approach.
- The most popular problem in Combinatorics, viz. Travelling Salesman Problem
- Other generic problems in discrete optimization, like the Knapsack Problem
- How metaheuristic approaches compare to heuristic solutions
- The nature-inspired class of metaheuristic approaches
- Ant Colony Optimization: its basis, modus operandi, algorithm and flow chart
- The R library to implement Ant Colony Optimization and other heuristic solutions
- Examples of Travelling Salesman Problems solved through different approaches
