A two-stage sequential approach for scheduling with lot-sizing decisions in the context of plastic injection systems
被引:7
作者:
Cervantes-Sanmiguel, K., I
论文数: 0引用数: 0
h-index: 0
机构:
Univ Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, Av Univ S-N, San Nicolas De Los Garza 66455, Nuevo Leon, MexicoUniv Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, Av Univ S-N, San Nicolas De Los Garza 66455, Nuevo Leon, Mexico
Cervantes-Sanmiguel, K., I
[1
]
Vargas-Flores, M. J.
论文数: 0引用数: 0
h-index: 0
机构:
Ctr Invest Matemat, Alianza Ctr 502, Monterrey 66629, NL, MexicoUniv Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, Av Univ S-N, San Nicolas De Los Garza 66455, Nuevo Leon, Mexico
Vargas-Flores, M. J.
[2
]
Ibarra-Rojas, O. J.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, Av Univ S-N, San Nicolas De Los Garza 66455, Nuevo Leon, MexicoUniv Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, Av Univ S-N, San Nicolas De Los Garza 66455, Nuevo Leon, Mexico
Ibarra-Rojas, O. J.
[1
]
机构:
[1] Univ Autonoma Nuevo Leon, Fac Ciencias Fis Matemat, Av Univ S-N, San Nicolas De Los Garza 66455, Nuevo Leon, Mexico
Scheduling;
Lot-sizing;
Integrated formulation;
Mixed-integer linear programming;
Sequential approach;
RESOURCE;
D O I:
10.1016/j.cie.2020.106969
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
This study addresses a planning problem for plastics injection systems, where final products are assembled of compatible plastic pieces. Additionally, the production of pieces requires the use of dedicated molds that are installed on compatible injection machines (leading to long setup times). Then, our Manufacturing Planning Problem determines the lot-size of each product in terms of the number of cycles for each piece-mold-machine combination and the scheduling of molds for each injection machine in a single planning period to maximize the total profit. We consider constraints for machines' available time and avoid mold overlapping on different machines. Moreover, we define a mixed-integer linear program for our problem, and we obtain high-quality solutions for medium-size instances using a commercial solver in minutes. Still, the convergence to optimal solutions for large instances is slower. In response, we propose a two-stage sequential approach that takes advantage of the mathematical formulation to obtain better solutions for large instances in short computational times.