Formulation of an IP-Based Model for Reactive Flow-Shop Scheduling Problem Subject to Arrival of New Orders

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In order to survive in a competitive environment, industries are required to adopt strategies that ensure their abilities to provide their customers with a product featured by good quality, low cost and short delivery time. Short term scheduling plays a pivotal role in this context by ensuring the operations to be executed and monitored in an optimal or sub-optimal manner which guarantees the product shipping within the customers’ due dates at lower cost and/or higher utilization of resources. However, the dynamic nature of the shop floor environment causes the predictive schedules to be no longer optimal or even feasible. Frequent disruptions occurring during the execution of the predictive schedule require the operations managers to be reactive to make appropriate decision considering the new situation. Adequate research works based on integer programming are available in literature to cope with static scheduling problems, but there is a dearth in integer programming based approaches for dynamic or reactive situations. The aim of this work is to formulate a model that solves the reactive flow-shop scheduling problem subject to arrival of new orders. Objective function for makespan minimization and the comprehensive equations for predictive and reactive schedules are presented with the necessary elaboration.

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616-621

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July 2015

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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[1] Wagner, H.M., An integer linear-programming model for machine scheduling. Naval Research Logistics Quarterly, 1959. 6(2): pp.131-140.

DOI: 10.1002/nav.3800060205

Google Scholar

[2] Fumero, Y., G. Corsano, and J.M. Montagna, A Mixed Integer Linear Programming model for simultaneous design and scheduling of flowshop plants. Applied Mathematical Modelling 2013. 37: p.1652–1664.

DOI: 10.1016/j.apm.2012.04.043

Google Scholar

[3] Zhen Zhou, Ada Che, and P.Y. b, A mixed integer programming approach for multi-cyclic robotic flowshop scheduling with time window constraints. Applied Mathematical Modelling 2012. 36: p.3621–3629.

DOI: 10.1016/j.apm.2011.10.032

Google Scholar

[4] Tseng, F.T., E.F. Stafford Jr, and J.N.D. Gupta, An empirical analysis of integer programming formulations for the permutation flowshop. Omega, 2004. 32(4): pp.285-293.

DOI: 10.1016/j.omega.2003.12.001

Google Scholar

[5] Sand, G. and S. Engell, Modeling and solving real-time scheduling problems by stochastic integer programming. Computers & Chemical Engineering, 2004. 28(6–7): pp.1087-1103.

DOI: 10.1016/j.compchemeng.2003.09.009

Google Scholar

[6] Méndez, C.A. and J. Cerdá, Dynamic scheduling in multiproduct batch plants. Computers & Chemical Engineering, 2003. 27(8–9): pp.1247-1259.

DOI: 10.1016/s0098-1354(03)00050-4

Google Scholar

[7] Sawik, T., Integer programming approach to reactive scheduling in make-to-order manufacturing. Mathematical and Computer Modelling, 2007. 46(11–12): pp.1373-1387.

DOI: 10.1016/j.mcm.2007.01.010

Google Scholar

[8] Balasubramanian, J. and I.E. Grossmann, Approximation to Multistage Stochastic Optimization in Multiperiod Batch Plant Scheduling under Demand Uncertainty. Industrial & Engineering Chemistry Research, 2004. 43(14): pp.3695-3713.

DOI: 10.1021/ie030308+

Google Scholar

[9] Vin, J.P. and M.G. Ierapetritou, A New Approach for Efficient Rescheduling of Multiproduct Batch Plants. Ind. Eng. Chem. Res., 2000. 39: pp.4228-4238.

DOI: 10.1021/ie000233z

Google Scholar

[10] Sawik, T., Scheduling in Supply Chains Using Mixed Integer Programming. John Wiley & Sons, Inc., Hoboken, New Jersey, (2011).

DOI: 10.1002/9781118029114

Google Scholar