TY - JOUR
T1 - Optimisation of multi-plant capacitated lot-sizing problems in an integrated supply chain network using calibrated metaheuristic algorithms
AU - Mohammadi, Maryam
AU - Musa, Siti Nurmaya
AU - Omar, Mohd Bin
PY - 2020
Y1 - 2020
N2 - In this paper, a mathematical model for a multi-item multi-period capacitated lot-sizing problem in an integrated supply chain network composed of multiple suppliers, plants and distribution centres is developed. The combinations of several functions such as purchasing, production, storage, backordering and transportation are considered. The objective is to simultaneously determine the optimal raw material order quantity, production and inventory levels, and the transportation amount, so that the demand can be satisfied with the lowest possible cost. Transfer decisions between plants are made when demand at a plant can be fulfilled by other production sites to cope with the under-capacity and stock-out problems of that plant. Since the proposed model is NP-hard, a genetic algorithm is used to solve the model. To validate the results, particle swarm optimisation and imperialist competitive algorithm are applied to solve the model as well. The results show that genetic algorithm offers better solution compared to other algorithms.
AB - In this paper, a mathematical model for a multi-item multi-period capacitated lot-sizing problem in an integrated supply chain network composed of multiple suppliers, plants and distribution centres is developed. The combinations of several functions such as purchasing, production, storage, backordering and transportation are considered. The objective is to simultaneously determine the optimal raw material order quantity, production and inventory levels, and the transportation amount, so that the demand can be satisfied with the lowest possible cost. Transfer decisions between plants are made when demand at a plant can be fulfilled by other production sites to cope with the under-capacity and stock-out problems of that plant. Since the proposed model is NP-hard, a genetic algorithm is used to solve the model. To validate the results, particle swarm optimisation and imperialist competitive algorithm are applied to solve the model as well. The results show that genetic algorithm offers better solution compared to other algorithms.
KW - Capacitated lot-sizing
KW - GA
KW - Genetic algorithm
KW - ICA.
KW - imperialist competitive algorithm
KW - Integrated supply chain
KW - Metaheuristic algorithms
KW - Multi-plant
KW - Optimisation
KW - Particle swarm optimization
KW - Production and distribution planning
KW - PSO
UR - http://www.scopus.com/inward/record.url?scp=85089178112&partnerID=8YFLogxK
U2 - 10.1504/IJOR.2020.110478
DO - 10.1504/IJOR.2020.110478
M3 - Article
AN - SCOPUS:85089178112
SN - 1745-7645
VL - 39
SP - 325
EP - 363
JO - International Journal of Operational Research
JF - International Journal of Operational Research
IS - 3
ER -