Multitask and multistage production planning and scheduling for process industries
成果类型：
Article
署名作者：
Gaglioppa, Francesco; Miller, Lisa A.; Benjaafar, Saif
署名单位：
University of Minnesota System; University of Minnesota Twin Cities; Target Corporation; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1080.0525
发表日期：
2008
页码：
1010-1025
关键词：
摘要：
We consider the planning and scheduling of production in a multitask/multistage batch manufacturing process typical of industries such as chemical manufacturing, food processing, and oil refining. We allow instances in which multiple sequences of tasks may be used to produce end products. We formulate the problem as a mixed-integer linear program and show that the linear programming relaxation has a large integrality gap and requires significant computational effort to solve to optimality for large instances. Using echelon inventory, we construct a new family of valid inequalities for this problem. The formulation with the additional constraints leads to a significantly tighter linear programming relaxation and to greatly reduced solution times for the mixed-integer linear program.