A model predictive framework for planning and scheduling problems: a case study of consumer goods supply chain

Bose, Sucharita; Pekny, Joseph F.

doi:10.1016/s0098-1354(00)00469-5

Cited by 94 publications

(42 citation statements)

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“…One subset of these, optimisation-models, have been widely used, especially when the scope of the problem is limited to selected supply chain functions such as planning [5] or scheduling [6]. Simulation models were envisaged for supply chains as far back as the 1950s [7], however it is only more recently that dynamic simulation-based decision support are attracting wide-spread attention, especially in the PSE community [8] [9] [10].…”

Section: Introductionmentioning

confidence: 99%

Critical evaluation of paradigms for modelling integrated supply chains

Dam

Adhitya

Srinivasan

et al. 2009

Computers & Chemical Engineering

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Contemporary problems in process systems engineering often require model-based decision support tool. Among the various modelling paradigms, equation-based models and agent-based models are widely used to develop dynamic models of systems. Which is the most appropriate modelling paradigm for a supply chain? In this paper, we seek to address this important question through a well-structured benchmarking process. First, we demonstrate that in the space of models, 'equations' and 'agents' are concepts of a different order, the former referring to the system description elements in the model while the latter emphasises the model elements. Thus conceptually, the two paradigms are not mutually exclusive. Next, in a case study different dynamic models of an oil refinery supply chain are developed, using different tools and approaches. By performing detailed experiments with two different models, it is demonstrated that the models are equivalent when compared using model definition, numerical results and recommended decisions. However, the modelling process itself is different and results in different model structures. By analysing the effort required to expand the models, allowing new scenarios to be tested, and reuse of model components, we identify the strengths of the two paradigms in the context of supply chain modelling.

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Section: Introductionmentioning

confidence: 99%

Critical evaluation of paradigms for modelling integrated supply chains

Dam

Adhitya

Srinivasan

et al. 2009

Computers & Chemical Engineering

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“…In Bose & Pekny (2000), MPC was applied to planning and scheduling problems, enabling the integration of uncertainty in material processing time, random equipment breakdowns or uncertainties in demand. Unlike other techniques applied to these problems that fix a moment in time, MPC allows the time evolution monitoring of the system, i.e., allows its dynamic analysis.…”

Section: Mpc Application In Supply Chainsmentioning

confidence: 99%

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

et al. 2015

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Aim of study: This work aims to provide an overview of Model Predictive Controllers (MPC) applications in supply chains, to describe the forest-based supply chain and to analyse the potential use and benefits of MPC in a case study concerning a biomass supply chain.Area of study: The proposed methods are being applied to a company located in Finland.Material and methods: Supply chains are complex systems where actions and partners’ coordination influence the whole system performance. The increase of competitiveness and need of quick responses to the costumers implies the use of efficient management techniques. The control theory, particularly MPC, has been successfully used as a supply chain management tool. MPC is able to deal with dynamic interactions between the partners and to globally optimize the supply chain performance in the presence of disturbances. However, as far as is authors’ knowledge, there are no applications of this methodology in the forest-based supply chains. This work proposes a control architecture to improve the performance of the forest supply chain. The controller is based on prediction models which are able to simulate the system and deal with disturbances.Main results: The preliminary results enable to evaluate the impacts of disturbances in the supply chain. Thus, it is possible to react beforehand, controlling the schedules and tasks’ allocation, or alert the planning level in order to generate a new plan.Research highlights: Overview of MPC applications in supply chains; forest-based supply chain description; case study presentation: wood biomass supply chain for energy production; MPC architecture proposal to decrease the operation times.Keywords: biomass; forest; Model Predictive Control; planning; supply chain.

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“…The few supply chain models that account for uncertainty follow different approaches. One part of the effort has been oriented through control theory in which uncertainty is modeled as disturbances in a dynamic model [20,21]. Another approach deals with uncertainty through fuzzy programming at the strategic level [22].…”

Section: Supply Chain Network Under Uncertaintymentioning

confidence: 99%

Supply Chain Network Optimization of the Canadian Forest Products Industry: A Critical Review

Shahi¹,

Pulkki²

2013

AJIBM

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The Canadian forest products industry has failed to retain its competitiveness in the global markets because of the under-utilization of its resources. Supply chain optimization models can identify the best possible fibre utilization strategies from multiple options of value creation based on fluctuating market conditions in the forest industries. This paper comprehensively reviews the literature related to supply chain models used both in general and specifically in the forest products industry. The optimization models use information from multiple agents (market demand attributes, flexible wood procurement and manufacturing processes, and resource characteristics), and share this information at each level in the supply chain network. However, the modeling of two-way flow of information (market to forests and vice-versa) for order promising and demand fulfillment through all facilities including manufacturing, processing, raw material procurement and inventory control is missing. The studies that focus on optimization are mostly deterministic in nature and do not account for uncertainty both in supply of raw materials and demand of forest products. Simulation and optimization models have been independently used for supply chain management in the past. The literature lacks an integrated approach that combines simulation and optimization models throughout the supply chain network of the Canadian forest products industry. Further studies should focus on developing simulation-based optimization models that will help in providing an operational planning tool that meets industrial expectations and provides much better solutions than current industrial practice.

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A model predictive framework for planning and scheduling problems: a case study of consumer goods supply chain

Cited by 94 publications

References 0 publications

Critical evaluation of paradigms for modelling integrated supply chains

Critical evaluation of paradigms for modelling integrated supply chains

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

Supply Chain Network Optimization of the Canadian Forest Products Industry: A Critical Review

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