Utilization Of Processing Time Windows To Enhance Planning And Scheduling In Short Term Multipurpose Batch Plants

The problem considered is short term scheduling in multipurpose batch plants when the main objective is adherence to due dates. The solution approach contemplates a two-phase procedure. The planning phase consists of processing time-windows for all the necessary batches to meet the products' demand. This information is extensively uses in the scheduling phase. Three approaches are considered in the last phase, a MILP formulation using uniform discrete time representation; constrained based search (CBS) and simulated annealing (SA). And assessment is made of these techniques in heavily constrained problems and how these approaches deal with equipment units sharing and constraints imposed by material balances and storage conditions. The advantages of the two-phase approach are shown in each case with illustrative examples. (C) 2000 Elsevier Science Ltd.The problem considered is short term scheduling in multipurpose batch plants when the main objective is adherence to due dates. The solution approach contemplates a two-phase procedure. The planning phase consists of processing time-windows for all the necessary batches to meet the products' demand. This information is extensively uses in the scheduling phase. Three approaches are considered in the last phase, a MILP formulation using uniform discrete time representation; constrained based search (CBS) and simulated annealing (SA). And assessment is made of these techniques in heavily constrained problems and how these approaches deal with equipment units sharing and constraints imposed by material balances and storage conditions. The advantages of the two-phase approach are shown in each case with illustrative examples.2402/07/15353359Graells, M., Espuña, A., Puigjaner, L., Evolutionary identification of best schedules for optimum production planning (1996) Second International Conference on Computer Integrated Manufacturing in the Process Industries, pp. 456-471. , J. C. Fransoo, & W. G. M. M. Rutten, Eindhoven, Holland(1997) Scheduler 4.0. User's Manual, , ILOGKeng, N.P., Yun, D.Y.Y., Rossi, M., Interaction sensitive planning system for job-shop scheduling (1988) Expert Systems and Intelligent Manufacturing, pp. 57-69. , M. D. Oliff, Amsterdam: ElsevierKondili, E., Pantelides, C.C., Sargent, R.W.H., A general algorithm for short term scheduling of batch operations - I. MILP formulation (1993) Computers & Chemical Engineering, 17 (2), pp. 211-227Papageorgiu, L.G., Pantelides, C.C., A hierarchical approach for campaign planning of multipurpose batch plants (1993) Computers & Chemical Engineering, 17 (2 SUPPL. ESCAPE), pp. 27-32Sadeh, N., (1991) Look-ahead Techniques for Micro-opportunistic Job Shop Scheduling, , Ph D thesis, CMU-CS-91-102, School of Computer Science, Carnegie Mellon Universit