A system of models contribution to production network (PN) theory

Kuehnle, Hermann

doi:10.1007/s10845-007-0062-4

Cited by 24 publications

(14 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nilsson and Darley (2006) proposed to combine CAS and MAS and to use the CAS as the theoretical approach and the MAS as the implementation method. Kuehnle (2007) considers agents as a part of the complex of interrelated models for ASC planning. Ivanov et al (2007a,b) and Ivanov (2009) consider agents as a part of the generic model constructions.…”

Section: State-of-the-artmentioning

confidence: 99%

A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations

Ivanov

Sokolov

Kaeschel

2010

European Journal of Operational Research

208

View full text Add to dashboard Cite

Section: State-of-the-artmentioning

confidence: 99%

A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations

Ivanov

Sokolov

Kaeschel

2010

European Journal of Operational Research

208

View full text Add to dashboard Cite

“…The goal is to get everyone in the production network into a common platform for logistics transactions and information systems [18]. This integration can result in significantly faster system responses to changes in marketplace events and patterns of demand.…”

Section: Planning In Production Networkmentioning

confidence: 99%

Applicability of ERP for Production Network Planning: A Case Study

Nehzati

Romsdal

Dreyer

et al. 2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

View full text Add to dashboard Cite

Abstract.A production network enables a company to develop capabilities to respond to diversity in national or regional demand, while at the same time integrate and coordinate their activities. Many companies have implemented enterprise resource planning (ERP) systems to overcome problems associated with coordination and planning in an organization, in recent years. In addition, advanced planning and scheduling (APS) systems have emerged to address the planning insufficiencies of ERP systems. However, due to complexity and competence dependency of these systems, advantages of them are overlooked by large organizations, and therefore ERP systems are still in use for planning. ERP systems are used in production networks for coordination of various plans and decisions across network partners. This paper aims to assess the fit and alignment between ERP functions and production network requirement for supporting production planning processes. Using a case study approach, the paper illustrates and discusses the applicability of ERP systems for planning in production networks. The case study showed that ERP systems have limited ability in coordinating order allocation in the network, detailed short term production planning and inter network distributions. It is concluded that use of ERP systems for network planning may in fact limit the network's ability to reap the full benefits associated with planning across several facilities in a network.

show abstract

“…While describing a complex system mathematically, this is almost impossible to consider in only one system model. As emphasized in Simchi-Levi et al (2004), Chandra and Grabis (2007), Kuehnle (2008), and Ivanov (2009), SC problems are tightly interlinked with each other and have multi-dimensional characteristics that require the application of different integrated frameworks of decision-making support. Isolated application of only one solution method leads to a narrowing in problem formulation, overdue constraints and sometimes unrealistic or impracticable goals.…”

Section: Introductionmentioning

confidence: 99%

“…Isolated application of only one solution method leads to a narrowing in problem formulation, overdue constraints and sometimes unrealistic or impracticable goals. A combined application of operations research (OR), control theory (CT), systems analysis, and agent-based modelling may potentially provide new insights into the SC domain (Sokolov and Yusupov 2004;Chandra and Grabis 2007;Kuehnle 2008;Ivanov 2009Ivanov , 2010.…”

Section: Introductionmentioning

confidence: 99%

Dynamic supply chain scheduling

Ivanov

Sokolov

2010

J Sched

View full text Add to dashboard Cite

Based on a combination of fundamental results of modern optimal program control theory and operations research, an original approach to supply chain scheduling is developed in order to answer the challenges of dynamics, uncertainty, and adaptivity. Both supply chain schedule generation and execution control are represented as an optimal program control problem in combination with mathematical programming and interpreted as a dynamic process of operations control within an adaptive framework. Hence, the problems and models of planning, scheduling, and adaptation can be consistently integrated on a unified mathematical axiomatic of modern control theory. In addition, operations control and flow control models are integrated and applicable for both discrete and continuous processes. The application of optimal control for supply chain scheduling becomes possible by formulating the scheduling model as a linear non-stationary finite-dimensional controlled differential system with the convex area of admissible control and a reconfigurable structure. For this model class, theorems of optimal control existence can be used regarding supply chain scheduling. The essential structural property of this model are the linear right parts of differential equations. This allows applying methods of discrete optimization for opti-D. Ivanov ( ) mal control calculation. The calculation procedure is based on applying Pontryagin's maximum principle and the resulting essential reduction of problem dimensionality that is under solution at each instant of time. The gained insights contribute to supply chain scheduling theory, providing advanced insights into dynamics of the whole supply chains (and not any dyadic relations in them) and transition from a partial "one-way" schedule optimization to the feedback loop-based dynamic and adaptive supply chain planning and scheduling.

show abstract

A system of models contribution to production network (PN) theory

Cited by 24 publications

References 28 publications

A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations

A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations

Applicability of ERP for Production Network Planning: A Case Study

Dynamic supply chain scheduling

Contact Info

Product

Resources

About