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Genetic Algorithm Based Floor Planning System
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Genetic Algorithms are widely used in many different optimization problems including layout design. The layout of the shelves play an important role in the total sales metrics for superstores since this affects the customers' shopping behaviour. This paper employed a genetic algorithm based approach to design shelf layout of superstores. The layout design problem was tackled by using a novel chromosome representation which takes many different parameters to prevent dead-ends and improve shelf visibility into consideration. Results show that the approach can produce reasonably good layout designs in very short amounts of time.
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Cited by 1 Pith paper
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Applies established DQN and A3C algorithms to train an agent to play Flappy Bird from raw game images via reinforcement learning.
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