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About Inventory Optimization in Efficient Supply
This document summarizes an article about using genetic algorithms to optimize inventory levels in a supply chain. The article discusses how genetic algorithms are inspired by biological evolution and natural selection. It describes how genetic algorithms work by encoding potential solutions as chromosomes, initializing a random population of chromosomes, and using crossover and mutation operators to generate new solutions and evolve the population toward better solutions. The article then applies these genetic algorithm concepts to determine optimal excess and shortage inventory levels across a three-stage supply chain model in order to minimize total supply chain costs.
Detailed Information
| Author: | ['Andres Felipe Cardozo Forero'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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