From process control to supply chain management: An overview of integrated decision making strategies

Abstract Optimal decision-making in a process industry is fundamental in order to guarantee optimality of operations and increase profits and performance of a company. Decision-making occurs at different levels, from process control to supply chain management. Traditionally, these decisions have been considered individually, with little or no interaction between each other. However, an integrated decision-making framework can guarantee solutions closer to optimality. Such integration usually results in complex and large scale problems that are difficult to solve. We provide an overview of integrated decision-making strategies and review recent advances in the area, highlighting promising works as well as the main challenges that have yet to be overcome.

[1]  Josef Kallrath,et al.  Planning and scheduling in the process industry , 2002, OR Spectr..

[2]  C. Pantelides,et al.  Optimal Campaign Planning/Scheduling of Multipurpose Batch/Semicontinuous Plants. 1. Mathematical Formulation , 1996 .

[3]  Nilay Shah,et al.  RTN-based rolling horizon algorithms for medium term scheduling of multipur-pose plants , 1997 .

[4]  Ignacio E. Grossmann,et al.  Simultaneous Cyclic Scheduling and Control of a Multiproduct CSTR Reactor , 2006 .

[5]  Gerd J. Hahn,et al.  Value-Based Performance and Risk Management in Supply Chains: A Robust Optimization Approach , 2012 .

[6]  M. Giannakis,et al.  A multi-agent based framework for supply chain risk management , 2011 .

[7]  Marianthi G. Ierapetritou,et al.  Multienterprise supply chain: Simulation and optimization , 2016 .

[8]  Fengqi You,et al.  Integrated Planning, Scheduling, and Dynamic Optimization for Batch Processes: MINLP Model Formulation and Efficient Solution Methods via Surrogate Modeling , 2014 .

[9]  Efstratios N. Pistikopoulos,et al.  A bilevel programming framework for enterprise-wide process networks under uncertainty , 2004, Comput. Chem. Eng..

[10]  Costas D. Maranas,et al.  Managing demand uncertainty in supply chain planning , 2003, Comput. Chem. Eng..

[11]  Ignacio E. Grossmann,et al.  A strategy for the integration of production planning and reactive scheduling in the optimization of a hydrogen supply network , 2003, Comput. Chem. Eng..

[12]  P. Castro,et al.  Optimal Periodic Scheduling of Batch Plants Using RTN-Based Discrete and Continuous-Time Formulations: A Case Study Approach , 2003 .

[13]  Fengqi You,et al.  Optimal supply chain design and operations under multi-scale uncertainties: Nested stochastic robust optimization modeling framework and solution algorithm , 2016 .

[14]  Ravindra D. Gudi,et al.  A Multilevel, Control-Theoretic Framework for Integration of Planning, Scheduling, and Rescheduling , 2005 .

[15]  Ana Paula Barbosa-Póvoa,et al.  Progresses and challenges in process industry supply chains optimization , 2012 .

[16]  M. Ierapetritou,et al.  Integration of scheduling and control for batch processes using multi‐parametric model predictive control , 2014 .

[17]  Peter M. Verderame,et al.  Integrated Operational Planning and Medium-Term Scheduling for Large-Scale Industrial Batch Plants , 2008 .

[18]  S. Talluri,et al.  Assessing the Efficiency of Risk Mitigation Strategies in Supply Chains , 2013 .

[19]  Hasan Pirkul,et al.  Planning and coordination of production and distribution facilities for multiple commodities , 2001, Eur. J. Oper. Res..

[20]  Rüdiger Franke,et al.  Production campaign planning including grade transition sequencing and dynamic optimization , 2005, Comput. Chem. Eng..

[21]  Marianthi G. Ierapetritou,et al.  Synchronous and asynchronous decision making strategies in supply chains , 2014, Comput. Chem. Eng..

[22]  Josef Kallrath,et al.  Optimal planning in large multi-site production networks , 2000, Eur. J. Oper. Res..

[23]  Marianthi G. Ierapetritou,et al.  Production planning and scheduling integration through augmented Lagrangian optimization , 2010, Comput. Chem. Eng..

[24]  Gonzalo Guillén-Gosálbez,et al.  A bi-criterion optimization approach for the design and planning of hydrogen supply chains for vehicle use , 2009 .

[25]  Iiro Harjunkoski,et al.  Production optimization for continuously operated processes with optimal operation and scheduling of multiple units , 2006, Comput. Chem. Eng..

[26]  Christopher S. Tang,et al.  The power of flexibility for mitigating supply chain risks , 2008 .

[27]  Josefa Mula,et al.  Quantitative models for supply chain planning under uncertainty: a review , 2009 .

[28]  A. Claudio Garavelli,et al.  Flexibility configurations for the supply chain management , 2003 .

[29]  I. Karimi,et al.  Agent-based supply chain management—1: framework , 2002 .

[30]  Marianthi G. Ierapetritou,et al.  Flexibility assessment and risk management in supply chains , 2015 .

[31]  Paul Davidsson,et al.  On the Integration of Agent-Based and Mathematical Optimization Techniques , 2007, KES-AMSTA.

[32]  Julian Benjamin,et al.  An Analysis of Inventory and Transportation Costs in a Constrained Network , 1989, Transp. Sci..

[33]  Clarence H. Martin,et al.  Integrated Production, Distribution, and Inventory Planning at Libbey-Owens-Ford , 1993 .

[34]  Gintaras V. Reklaitis,et al.  Perspectives on model based integration of process operations , 1996 .

[35]  N.P. Padhy,et al.  Unit commitment-a bibliographical survey , 2004, IEEE Transactions on Power Systems.

[36]  I. Grossmann,et al.  A Decomposition Method for the Simultaneous Planning and Scheduling of Single-Stage Continuous Multiproduct Plants , 2006 .

[37]  Lazaros G. Papageorgiou,et al.  Supply chain optimisation for the process industries: Advances and opportunities , 2009, Comput. Chem. Eng..

[38]  Atul P. Kanyalkar,et al.  An integrated aggregate and detailed planning in a multi-site production environment using linear programming , 2005 .

[39]  Gintaras V. Reklaitis,et al.  Simulation-based optimization with surrogate models - Application to supply chain management , 2005, Comput. Chem. Eng..

[40]  T. Comes,et al.  A critical review on supply chain risk – Definition, measure and modeling ☆ , 2015 .

[41]  Fengqi You,et al.  Novel Optimization Model and Efficient Solution Method for Integrating Dynamic Optimization with Process Operations of Continuous Manufacturing Processes , 2015 .

[42]  Ignacio E. Grossmann,et al.  Simultaneous cyclic scheduling and optimal control of polymerization reactors , 2007 .

[43]  Antonio Espuña Camarasa,et al.  Scenario-based price negotiations vs. game theory in the optimization of coordinated supply chains , 2015 .

[44]  Marianthi G. Ierapetritou,et al.  Integration of Scheduling and Control with Closed Loop Implementation , 2012 .

[45]  Alain Martel,et al.  Modeling approaches for the design of resilient supply networks under disruptions , 2012 .

[46]  Jayashankar M. Swaminathan,et al.  Modeling Supply Chain Dynamics: A Multiagent Approach , 1998 .

[47]  Patroklos Georgiadis,et al.  The effect of environmental parameters on product recovery , 2004, Eur. J. Oper. Res..

[48]  Christian Schulz,et al.  Approximation of an ideal online scheduler for a multiproduct batch plant , 2000 .

[49]  Zukui Li,et al.  Integrated production planning and scheduling using a decomposition framework , 2009 .

[50]  Ignacio E. Grossmann,et al.  Lagrangean heuristic for the scheduling and control of polymerization reactors , 2008 .

[51]  Danielle Zyngier,et al.  Hierarchical decomposition heuristic for scheduling: Coordinated reasoning for decentralized and distributed decision-making problems , 2008, Comput. Chem. Eng..

[52]  Fengqi You,et al.  Integrated Scheduling and Dynamic Optimization of Complex Batch Processes with General Network Structure Using a Generalized Benders Decomposition Approach , 2013 .

[53]  Michael Baldea,et al.  Optimal Process Operations in Fast-Changing Electricity Markets: Framework for Scheduling with Low-Order Dynamic Models and an Air Separation Application , 2016 .

[54]  Ignacio E. Grossmann,et al.  Advances in mathematical programming models for enterprise-wide optimization , 2012, Comput. Chem. Eng..

[55]  María Analía Rodríguez,et al.  Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part II: A Lagrangean decomposition algorithm , 2014, Comput. Chem. Eng..

[56]  Marvin D. Troutt,et al.  Dynamic simulation of the supply chain for a short life cycle product - Lessons from the Tamagotchi case , 2004, Comput. Oper. Res..

[57]  Ana Paula Barbosa-Póvoa,et al.  Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty , 2015 .

[58]  Marianthi G. Ierapetritou,et al.  An integrated framework for scheduling and control using fast model predictive control , 2015 .

[59]  Cheng-Liang Chen,et al.  Multiobjective Optimization for a Multienterprise Supply Chain Network , 2003 .

[60]  X. Zhu,et al.  Novel continuous time MILP formulation for multipurpose batch plants. 2. Integrated planning and scheduling , 2001 .

[61]  Marianthi G. Ierapetritou,et al.  Erratum to “An Integrated Framework for Scheduling and Control Using Fast Model Predictive Control” , 2016 .

[62]  Ana Paula Barbosa-Póvoa,et al.  Process Supply Chains Management – Where are We? Where to Go Next? , 2014, Front. Energy Res..

[63]  C. Maravelias,et al.  An attainable region approach for production planning of multiproduct processes , 2007 .

[64]  Cheng-Liang Chen,et al.  Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices , 2004, Comput. Chem. Eng..

[65]  Marianthi G. Ierapetritou,et al.  Hybrid simulation based optimization framework for centralized and decentralized supply chains , 2014 .

[66]  B. Beamon.  Supply chain design and analysis:: Models and methods , 1998 .

[67]  G. Schilling,et al.  Optimal periodic scheduling of multipurpose plants , 1999 .

[68]  Paul van Beek,et al.  Modelling and simulating multi-echelon food systems , 2000, Eur. J. Oper. Res..

[69]  Nikolaos V. Sahinidis,et al.  Simulation optimization: a review of algorithms and applications , 2014, 4OR.

[70]  Fengqi You,et al.  A computationally efficient simulation-based optimization method with region-wise surrogate modeling for stochastic inventory management of supply chains with general network structures , 2016, Comput. Chem. Eng..

[71]  Benoit Montreuil,et al.  Networked manufacturing:: The impact of information sharing , 1999 .

[72]  Marianthi G. Ierapetritou,et al.  Optimal design of sustainable chemical processes and supply chains: A review , 2012, Comput. Chem. Eng..

[73]  Nilay Shah,et al.  Optimal periodic scheduling of multipurpose batch plants , 1993, Ann. Oper. Res..

[74]  María Analía Rodríguez,et al.  Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models , 2014, Comput. Chem. Eng..

[75]  Xue Zhong Wang,et al.  A multi-agent system for chemical supply chain simulation and management support , 2002, OR Spectr..

[76]  Gintaras V. Reklaitis,et al.  Simulation-optimization approach to clinical trial supply chain management with demand scenario forecast , 2012, Comput. Chem. Eng..

[77]  Benita M. Beamon,et al.  A multi-objective approach to simultaneous strategic and operational planning in supply chain design , 2000 .

[78]  Hartmut Stadtler,et al.  Supply chain management and advanced planning--basics, overview and challenges , 2005, Eur. J. Oper. Res..

[79]  Y. B. Park,et al.  An integrated approach for production and distribution planning in supply chain management , 2005 .

[80]  Fengqi You,et al.  Integrated Scheduling and Dynamic Optimization by Stackelberg Game: Bilevel Model Formulation and Efficient Solution Algorithm , 2014 .

[81]  Nikolaos V. Sahinidis,et al.  Derivative-free optimization: a review of algorithms and comparison of software implementations , 2013, J. Glob. Optim..

[82]  Marianthi G. Ierapetritou,et al.  Integrated production planning and scheduling optimization of multisite, multiproduct process industry , 2012, Comput. Chem. Eng..

[83]  Ingolf Voigt,et al.  Co‐firing technology for the preparation of asymmetric oxygen transporting membranes based on BSCF and Zr‐doped BSCF , 2014 .

[84]  C. Maranas,et al.  A Hierarchical Lagrangean Relaxation Procedure for Solving Midterm Planning Problems , 1999 .

[85]  H. Nachtmann,et al.  SUPPLY CHAIN INFORMATION SHARING IN A VENDOR MANAGED INVENTORY PARTNERSHIP , 2004 .

[86]  Ignacio E. Grossmann,et al.  Enterprise‐wide optimization: A new frontier in process systems engineering , 2005 .

[87]  Stephen C. Graves,et al.  Process Flexibility in Supply Chains , 2003, Manag. Sci..

[88]  Marianthi G. Ierapetritou,et al.  Supply chain management using an optimization driven simulation approach , 2013 .

[89]  Dan Wu,et al.  Hierarchical approach for production planning and scheduling under uncertainty , 2005 .

[90]  G. Reklaitis,et al.  A simulation based optimization approach to supply chain management under demand uncertainty , 2004, Comput. Chem. Eng..

[91]  Christine S. Grant,et al.  Effects of Antioxidants on the Thermal Degradation of a Polyol Ester Lubricant Using GPC , 2006 .

[92]  Josefa Mula,et al.  Mathematical programming models for supply chain production and transport planning , 2010, Eur. J. Oper. Res..

[93]  F. Chan,et al.  Comparative study of adaptability and flexibility in distributed manufacturing supply chains , 2010, Decis. Support Syst..

[94]  Alan J. Stenger,et al.  The impact of inventory and flow planning parameters on supply chain performance: An exploratory study , 2001 .

[95]  Oscar Mauricio Hernandez Rodriguez,et al.  Stability analysis of core-annular flow and neutral stability wave number , 2008 .

[96]  C. Pantelides,et al.  Optimal Campaign Planning/Scheduling of Multipurpose Batch/Semicontinuous Plants. 2. A Mathematical Decomposition Approach , 1996 .

[97]  Fengqi You,et al.  Integration of Scheduling and Dynamic Optimization of Batch Processes under Uncertainty: Two-Stage Stochastic Programming Approach and Enhanced Generalized Benders Decomposition Algorithm , 2013 .

[98]  Lorenz T. Biegler,et al.  Multi-scale optimization for process systems engineering , 2014, Comput. Chem. Eng..