TY - JOUR

T1 - A parallel algorithm for solving unfriendly beehive problems

AU - Rofkar, J. D.

AU - Takefuji, Y.

PY - 1992/5

Y1 - 1992/5

N2 - 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.

AB - 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.

KW - Parallel algorithm

KW - Unfriendly Beehive Problem

KW - combinatorial optimization

UR - http://www.scopus.com/inward/record.url?scp=0026869971&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026869971&partnerID=8YFLogxK

U2 - 10.1016/0925-2312(92)90006-B

DO - 10.1016/0925-2312(92)90006-B

M3 - Article

AN - SCOPUS:0026869971

VL - 4

SP - 167

EP - 179

JO - Neurocomputing

JF - Neurocomputing

SN - 0925-2312

IS - 3-4

ER -