TY - GEN
T1 - Systems engineering to improve cows' artificial insemination services
AU - Halachmi, I.
AU - Shneider, B.
AU - Gilad, D.
AU - Eben Chaime, M.
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Engineering and management tools and mathematical optimization are applied in this study to plan the work of the agents of the cow artificial insemination service (inseminator) in Israel. Time is crucial in insemination as the chances of conception decline with increasing delay between the start of estrus and insemination. About 1,090 artificial inseminations of cows are performed daily in Israel. They involve 412 farms in 283 villages, and are performed by 29 inseminators; the work plan should balance the work load among the inseminators. To this ends, the working time of an inseminator in each village is required. Thus, a model to predict the working time in a village was developed. Subsequently, a mathematical optimization model was designed and solved, which aims to allocate customers to trips and to determine the itinerary of each trip so as to minimize total distance/time. The main benefits included a 21.4% reduction in total traveling time, and a 55% reduction in the difference between the lengths of the longest and shortest working days. Moreover, the longest delay in reaching an estrous cow is reduced from 7.6 to 5.9 h, i.e. by 1.7 h, which may increase the conception ratio by some 7%. In addition, the trade-off between work balance and total traveling time was studied.
AB - Engineering and management tools and mathematical optimization are applied in this study to plan the work of the agents of the cow artificial insemination service (inseminator) in Israel. Time is crucial in insemination as the chances of conception decline with increasing delay between the start of estrus and insemination. About 1,090 artificial inseminations of cows are performed daily in Israel. They involve 412 farms in 283 villages, and are performed by 29 inseminators; the work plan should balance the work load among the inseminators. To this ends, the working time of an inseminator in each village is required. Thus, a model to predict the working time in a village was developed. Subsequently, a mathematical optimization model was designed and solved, which aims to allocate customers to trips and to determine the itinerary of each trip so as to minimize total distance/time. The main benefits included a 21.4% reduction in total traveling time, and a 55% reduction in the difference between the lengths of the longest and shortest working days. Moreover, the longest delay in reaching an estrous cow is reduced from 7.6 to 5.9 h, i.e. by 1.7 h, which may increase the conception ratio by some 7%. In addition, the trade-off between work balance and total traveling time was studied.
KW - Artificial insemination (AI)
KW - Cows
KW - Mathematical optimization
KW - Production-line balancing
KW - Traveling salesman problem
KW - Vehicle routing problem
UR - http://www.scopus.com/inward/record.url?scp=84890823925&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84890823925
SN - 9789086861125
T3 - Precision Livestock Farming 2009 - Papers Presented at the 4th European Conference on Precision Livestock Farming
SP - 215
EP - 223
BT - Precision Livestock Farming 2009 - Papers Presented at the 4th European Conference on Precision Livestock Farming
T2 - 4th European Conference on Precision Livestock Farming, ECPLF 2009
Y2 - 6 July 2009 through 8 July 2009
ER -