An efficient optimal solution to the coil sequencing problem in electro-galvanizing line

This paper studies a coil sequencing problem that arises from electro-galvanizing line in steel industry. The problem is to find a processing sequence of steel coils such that the switching costs between consecutive coils are minimized while satisfying technical restrictions. The problem can be decomposed into several independent sub-problems, each corresponding to a turn which is a sequence of continuously processed coils with the same post-processing requirement. The coils in each turn can be further divided into several families each consisting of the coils with the same width. Based on analysis of the problem properties, a two-phase polynomial algorithm is developed to obtain an optimal turn. The sequence of coils in a family with given boundary coils (first and last coils) is determined in the first phase using a polynomial dynamic programming algorithm. In the second phase, the optimal turn is formed by another polynomial dynamic programming algorithm which takes the boundary coils for each family as state variables. The efficiency of the proposed algorithm is demonstrated through computational experiments.

[1]  Michel Gendreau,et al.  The hot strip mill production scheduling problem: A tabu search approach , 1998, Eur. J. Oper. Res..

[2]  Lixin Tang,et al.  A branch-and-price algorithm to solve the molten iron allocation problem in iron and steel industry , 2007, Comput. Oper. Res..

[3]  Lixin Tang,et al.  A review of planning and scheduling systems and methods for integrated steel production , 2001, Eur. J. Oper. Res..

[4]  Jacques Teghem,et al.  A mixed-integer linear programming model for the continuous casting planning , 2006 .

[5]  Soo Y. Chang,et al.  A lot grouping algorithm for a continuous slab caster in an integrated steel mill , 2000 .

[6]  R. Bellman Dynamic programming. , 1957, Science.

[7]  Vitaly A. Strusevich,et al.  Single machine scheduling and due date assignment with positionally dependent processing times , 2009, Eur. J. Oper. Res..

[8]  Shijie Sun,et al.  Scheduling linear deteriorating jobs with rejection on a single machine , 2009, Eur. J. Oper. Res..

[9]  T.C.E. Cheng,et al.  Parallel-machine batching and scheduling to minimize total completion time , 1996 .

[10]  Andrew J. Davenport,et al.  Finishing Line Scheduling in the steel industry , 2004, IBM J. Res. Dev..

[11]  Ho Soo Lee,et al.  Primary production scheduling at steelmaking industries , 1996, IBM J. Res. Dev..

[12]  Lixin Tang,et al.  A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex , 2000, Eur. J. Oper. Res..

[13]  X. Wang,et al.  An iterated local search heuristic for the capacitated prize-collecting travelling salesman problem , 2008, J. Oper. Res. Soc..

[14]  R. A. Zemlin,et al.  Integer Programming Formulation of Traveling Salesman Problems , 1960, JACM.

[15]  William J. Cook,et al.  Solution of a Large-Scale Traveling-Salesman Problem , 1954, 50 Years of Integer Programming.

[16]  R. Gomory,et al.  Sequencing a One State-Variable Machine: A Solvable Case of the Traveling Salesman Problem , 1964 .

[17]  Paolo Toth,et al.  State-space relaxation procedures for the computation of bounds to routing problems , 1981, Networks.

[18]  M. Angeles Pérez Alarcó,et al.  Scheduling in a continuous galvanizing line , 2009, Comput. Oper. Res..