TY - JOUR
T1 - Collecting and Delivering Fattened Pigs to the Abattoir
AU - Plà-Aragonés, Lluís Miquel
AU - Bao, Yun
AU - Llagostera, Pol
AU - Juan, Angel
AU - Panadero, Javier
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/5/29
Y1 - 2024/5/29
N2 - In the context of pig farming, this paper addresses the optimization problem of collecting fattened pigs from farms to deliver them to the abattoir. Assuming that the pig sector is organized as a competitive supply chain with narrow profit margins, our aim is to apply analytics to cope with the uncertainty in production costs and revenues. Motivated by a real-life case, the paper analyzes a rich Team Orienteering Problem (TOP) with a homogeneous fleet, stochastic demands, and maximum workload. After describing the problem and reviewing the related literature, we introduce the PJS heuristic. Our approach is first compared with exact methods, which are revealed as computationally unfeasible. Later, a scenario analysis based on a real instance was performed to gain insight into the practical aspects. Our findings demonstrate a positive correlation between the number of alternative routes explored, the number of trips, the transportation cost, and the maximum reward. Regarding the variability in the number of pigs to collect, when a truck can visit more than one farm, better solutions can be found with higher variability since the load can be combined more efficiently.
AB - In the context of pig farming, this paper addresses the optimization problem of collecting fattened pigs from farms to deliver them to the abattoir. Assuming that the pig sector is organized as a competitive supply chain with narrow profit margins, our aim is to apply analytics to cope with the uncertainty in production costs and revenues. Motivated by a real-life case, the paper analyzes a rich Team Orienteering Problem (TOP) with a homogeneous fleet, stochastic demands, and maximum workload. After describing the problem and reviewing the related literature, we introduce the PJS heuristic. Our approach is first compared with exact methods, which are revealed as computationally unfeasible. Later, a scenario analysis based on a real instance was performed to gain insight into the practical aspects. Our findings demonstrate a positive correlation between the number of alternative routes explored, the number of trips, the transportation cost, and the maximum reward. Regarding the variability in the number of pigs to collect, when a truck can visit more than one farm, better solutions can be found with higher variability since the load can be combined more efficiently.
KW - abattoir
KW - fattened pigs
KW - PJS heuristic
KW - team orienteering problem
KW - vertical integration
UR - http://www.scopus.com/inward/record.url?scp=85195961341&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/5cfc38f1-fb7e-3985-acf2-71fced1031fb/
U2 - 10.3390/ani14111608
DO - 10.3390/ani14111608
M3 - Article
C2 - 38891655
AN - SCOPUS:85195961341
SN - 2076-2615
VL - 14
JO - Animals
JF - Animals
IS - 11
M1 - 1608
ER -