Multi-bucket optimization for integrated planning and scheduling in the perishable dairy supply chain

Sel C., BİLGEN B., Bloemhof-Ruwaard J., van der Vorst J.

Computers and Chemical Engineering, vol.77, pp.59-73, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 77
  • Publication Date: 2015
  • Doi Number: 10.1016/j.compchemeng.2015.03.020
  • Journal Name: Computers and Chemical Engineering
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.59-73
  • Keywords: Integrated planning and scheduling, Mixed integer linear programming, Constraint programming, Hybrid approach, Perishability, Dairy supply chain, MIXED-INTEGER, PARALLEL MACHINES, BATCH PLANTS, MODELS, ALGORITHM, MANAGEMENT
  • Dokuz Eylül University Affiliated: Yes


© 2015 Elsevier Ltd.This paper considers a dairy industry problem on integrated planning and scheduling of set yoghurt production. A mixed integer linear programming formulation is introduced to integrate tactical and operational decisions and a heuristic approach is proposed to decompose time buckets of the decisions. The decomposition heuristic improves computational efficiency by solving big bucket planning and small bucket scheduling problems. Further, mixed integer linear programming and constraint programming methodologies are combined with the algorithm to show their complementary strengths. Numerical studies using illustrative data with high demand granularity (i.e., a large number of small-sized customer orders) demonstrate that the proposed decomposition heuristic has consistent results minimizing the total cost (i.e., on average 8.75% gap with the best lower bound value found by MILP) and, the developed hybrid approach is capable of solving real sized instances within a reasonable amount of time (i.e., on average 92% faster than MILP in CPU time).