## Abstract

This paper presents a general purpose algorithm for solving the Unfriendly Beehive Game. The proposed algorithm will utilize an artificial neural network to solve the problem. The neural network will use a simple partial differential (motion) equation expressed in terms of its natural constraints. Each constraint within the equation represents a simple connection to an artificial neuron. Each connection strength (or synaptic strength) is weighted by multiplicative constants and summed together. The result is an input that is adjusted in the direction that decreases the error or conflict. Using this information, the system derives a simple binary state output in an attempt to solve the puzzle. Given an overall time slot in which to resolve all conflicts, the system iteratively strives to arrive at the state of the global minimum. The proposed algorithm will be able to solve a variety of real-world problems, including: facility layouts for maximizing productivity and safety, classroom assignment for minimizing pupil conflict, crop and plant placement for maximizing yields, and chemical placement within shipping boxes to reduce the possibility of chemical interactions.

Original language | English |
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Pages (from-to) | 167-179 |

Number of pages | 13 |

Journal | Neurocomputing |

Volume | 4 |

Issue number | 3-4 |

DOIs | |

Publication status | Published - 1992 May |

Externally published | Yes |

## Keywords

- Parallel algorithm
- Unfriendly Beehive Problem
- combinatorial optimization

## ASJC Scopus subject areas

- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence