Towards a simulation-based optimization approach to integrate supply chain planning and control

Die Kalksandsteinherstellung weist aufgrund prozesstechnisch und zeitlich divergierender Teilprozesse einen hohen Planungs- sowie Steuerungsaufwand auf. Durch Einsatz eines simulationsgestützten Optimierungsverfahrens kann diese Komplexität bewältigt werden. Um bei hoher Lösungsqualität eine Laufzeit zu erreichen, die einen operativen Einsatz des Verfahrens gestattet, wird auf Basis einer vorangegangenen Studie ein Dekompositionsansatz implementiert und dessen Eignung durch Testläufe validiert.   Calcium silicate masonry production requires a great deal of planning and control due to the fact that subprocesses vary in terms of process technology and time. To overcome this complexity, a simulation-based optimization approach is applied. As a short runtime that allows the method to be used operationally and yet still offers a high quality of solution is crucial, a decomposition approach is implemented on the basis of a previous study and its suitability is validated by means of test runs.

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Hybrid simulation based optimization approach for supply chain management

Computers & Chemical Engineering ◽

10.1016/j.compchemeng.2012.06.045 ◽

2012 ◽

Vol 47 ◽

pp. 183-193 ◽

Cited By ~ 47

Author(s):

Amalia Nikolopoulou ◽

Marianthi G. Ierapetritou

Keyword(s):

Supply Chain ◽

Supply Chain Management ◽

Hybrid Simulation ◽

Optimization Approach ◽

Chain Management ◽

Simulation Based ◽

Simulation Based Optimization

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Collaborative Demand and Supply Planning Networks

Industrial Engineering ◽

10.4018/978-1-4666-1945-6.ch008 ◽

2012 ◽

pp. 108-116

Author(s):

Hans-Henrik Hvolby ◽

Kenn Steger-Jensen ◽

Erlend Alfnes ◽

Heidi C. Dreyer

Keyword(s):

Supply Chain ◽

Research Council ◽

Supply Chain Planning ◽

Demand And Supply ◽

Manufacturing Planning ◽

Planning And Control ◽

Exchange Information ◽

Supply Planning ◽

And Control ◽

House Production

The focus of manufacturing planning and control has gradually expanded from (in-house) production activities towards all manufacturing and logistic activities in the supply chain. Planning of in-house operations is still very important, but the trends towards increased use of outsourcing and mass customisation require that customers and suppliers are able to exchange information frequently to cut down costs and lead time while quickly adapting their manufacturing and logistics operations to market/customer requirements. Many vendors offer systems to plan and control in-house operations, whereas only a few large vendors (such as Oracle, SAP and I2) offer supply chain planning systems. This limits the ability for SMEs to exploit the supply chain planning options. This chapter discuss current supply chain planning solutions and presents a more simple and adaptive concept to be used in both SMEs and larger enterprises. The research presented in this chapter is funded by the EU Union via the EmpoSME, ValuePole projects, and by the Research Council of Norway via the SFI Norman project.

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Grocery retail supply chain planning and control: Impact of consumer trends and enabling technologies

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2018.08.386 ◽

2018 ◽

Vol 51 (11) ◽

pp. 612-617

Author(s):

Logan R. Vallandingham ◽

Quan Yu ◽

Nakul Sharma ◽

Jo W. Strandhagen ◽

Jan Ola Strandhagen

Keyword(s):

Supply Chain ◽

Supply Chain Planning ◽

Planning And Control ◽

Enabling Technologies ◽

And Control

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Evaluation of Communication in Multiagent Systems for Supply Chain Planning and Control

2014 IEEE 26th International Conference on Tools with Artificial Intelligence ◽

10.1109/ictai.2014.68 ◽

2014 ◽

Cited By ~ 1

Author(s):

Faten Ben Hmida ◽

Wided Lejouad Chaari ◽

Remy Dupas ◽

Anne Seguy

Keyword(s):

Supply Chain ◽

Multiagent Systems ◽

Supply Chain Planning ◽

Planning And Control ◽

And Control

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Opposites Attract: An Approach to Collaborative Supply Chain Management between Semiconductor and Automotive Companies

Industrial and Systems Engineering Review ◽

10.37266/iser.2013v1i1.pp13-30 ◽

2013 ◽

Vol 1 (1) ◽

pp. 13-30

Author(s):

Judith Aelker ◽

Verena Meister ◽

Christoph Forster ◽

Matthias Zapp ◽

Thomas Bauernhansl

Keyword(s):

Supply Chain ◽

Supply Chain Management ◽

Automotive Industry ◽

Gap Analysis ◽

Semiconductor Industry ◽

Supply Chain Planning ◽

Chain Management ◽

Planning And Control ◽

Weak Points ◽

And Control

This article illustrates the differences between the semiconductor and the automotive industry and the subsequent challenges to their common supply chain. The weak points at the interfaces between the two supply chains will systematically be identified and assessed. Based on this analysis, a toolkit for collaborative supply chain planning and execution between the automotive and the semiconductor industry is presented. A fit/gap analysis assesses the measures and their potential to solve the supply chain challenges in a systematic manner. The model is built upon existing supply chain management frameworks and defines a set of specific optimization measures for the problem at hand. These are designed to ensure a better alignment of planning and control processes between the automotive and the semiconductor industry.

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Product Centric Organization of After-Sales Supply Chain Planning and Control

Behavioral Operations in Planning and Scheduling ◽

10.1007/978-3-642-13382-4_9 ◽

2010 ◽

pp. 187-198

Author(s):

Jan Holmström ◽

Naoufel Cheikhrouhou ◽

Gael Farine ◽

Kary Främling

Keyword(s):

Supply Chain ◽

Supply Chain Planning ◽

Planning And Control ◽

And Control

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A simulation-based optimization approach to integrated inventory management of a sawlog supply chain with demand uncertainty

Canadian Journal of Forest Research ◽

10.1139/cjfr-2014-0373 ◽

2015 ◽

Vol 45 (10) ◽

pp. 1313-1326 ◽

Cited By ~ 16

Author(s):

Shashi Shahi ◽

Reino Pulkki

Keyword(s):

Supply Chain ◽

Forest Management ◽

Forest Products ◽

Management Unit ◽

Production Unit ◽

Chain Model ◽

Optimization Approach ◽

Simulation Based ◽

Simulation Based Optimization ◽

Flow Of Information

This paper develops a simulation-based optimization supply chain model for supplying sawlogs to a sawmill from a forest management unit. The simulation model integrates the two-way flow of information and materials under the stochastic demand of the sawmill production unit. The dynamic optimization model finds the optimum inventory policy (s, S) that minimizes the total inventory cost for the three supply chain agents — sawmill storage, merchandizing yard, and forest management unit. The model is used to analyze a real sawmill case study in northwestern Ontario, Canada. It was found that the merchandizing yard absorbs shocks of uncertain demand from the sawmill production unit and reduces idle time, but it increases the total cost of the supply chain by $11 802 (about 42%). The optimized model predicts that only 3.5 days of inventory is required at the sawmill storage. The simulation-based optimization supplier model will help in decision-making at the tactical and operational level in the forest products industry supply chain through a two-way flow of information and materials.

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