Making Strategic Supply Chain Capacity Planning more Dynamic to cope with Hyperconnected and Uncertain Environments (original) (raw)
Related papers
2008
For the practical use of supply chain management powerful planning tools are needed to support production and logistics decisions at various planning levels. In our paper, we focus on medium-term supply network planning. As a real application, the production of a chemical additive in a multi-site production and distribution network is considered. Supply network planning is an exceedingly complex task which can only be accomplished with the support of computer based systems. Instead of using an off-the-shelf planning tool, the company decided to develop its own linear programming based optimization model. This model allows the consideration of various application features, e.g. the use of alternate production resources or the generation of electrical energy as a side product. The optimization model has proven to be of major value for both strategic and operational decisions. The model is now in full use at three production-distribution networks in different parts of the world.
Decision support framework for supply chain planning with flexible demand
International Journal of Production Research, 2009
The most challenging issue of today's production management is certainly to manage networked organisations under an uncertain demand so that to provide a good service to the customer at low cost. In this article, a model of the decision making parameters involved in this management process is suggested, on the base of case studies. A mixed integer linear planning model embedded in a framework simulating a rolling horizon planning process is described on the base of this analysis. The model takes into account the capabilities of reaction of the planned system and of its environment (suppliers, subcontractors and customers), as well as the corresponding costs. The suggested simulation framework may assist the decision maker for coping with an uncertain or flexible demand, using various planning strategies. Some possible applications of this simulation framework are given in order to illustrate how it can help to solve various types of practical planning problems.
A prototype decision support system for strategic planning under uncertainty
International Journal of Physical Distribution & Logistics Management, 2000
Strategic planning of the supply chain is an important decision problem determining the long-term survival and prosperity of companies in the manufacturing, retail, and other industrial sectors. In general such companies rely on their information systems to acquire the essential data that are used in their planning models. The interaction of information systems and decision modelling, and the progressive transformation of data, into information, and knowledge is a key process underlying any decision support system (DSS) for strategic, tactical or operational planning. In this paper we consider a DSS for supply chain planning (SCP) decisions. The SCP system has an embedded decision engine that uses a two-stage stochastic program as a paradigm for optimisation under uncertainty. The system has been used for decision making in diverse domains, including automotive manufacturing and consumer products.
A decision support system for the supply chain configuration
2003
Abstract The design of a supply chain network provides the main structure for supply chain operations, since the network is a key element in the competitiveness and investments of an extended production system. The configuration of the network is essential for business to pursue a competitive advantage. We adopt a methodology based on three layers. In the first layer, the performance of the entities candidate to join the network is evaluated and efficient elements are individuated.
A two-phase multi-criteria decision support system for supply chain management
International Journal of Operational Research, 2010
Multi-criteria decision-making techniques have been used to solve a range of real world problems in management science and specific supply chain management (SCM) problems (e.g. supply chain design and reconfiguration, purchasing, scheduling, supplier selection). The results obtained are encouraging. Nevertheless, robust approaches for solving multi-criteria supply chain problems are still in progress, and more research is needed before an effective and operational framework can be developed. The proposed approach introduces a two-phase hierarchical approach to solve a multi-criteria SCM problem integrating both strategic and tactical decisions where the supply chain is evaluated based on the supply chain operations reference model. The latter considers various metrics such as delivery reliability, flexibility, responsiveness and cost. The first phase evaluates different supply chains configurations using analytic hierarchy process. The second phase solves the network for the optimal safety stock placement using dynamic programming. The output from this twophase process is a supply chain network configuration that has the right amount of safety stocks at the right place to absorb variability in demand.
A Multi-Agent Decision Support System for Dynamic Supply Chain Organization
In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the supply chain organization.
Decision Support Model for Supply Chain Management
Teme, 2021
The purpose of this paper is the creation of a model for supply chain performance optimization and the development of a prototype of the decision support system. The study covered an efficient and agile supply chain type. The Analytic Hierarchy Process was used (AHP) for the evaluation and ranking of supply chains. The research on this topic have dealt with the evaluation and ranking of suppliers within supply chains not considering the characteristics of different types of supply chains. The contribution of this work is in the development of a new model that enables the evaluation and ranking of supply chains considering the priorities of key performance indicators in different types of supply chains, providing management with the support in decision making through simulation and the finding of optimum solutions for the specific supply chain type, as well as the possibility of evaluation and ranking of different supply chain types on the basis of weighted overall performance of each supply chain. Developed and suggested models provide company management with monitoring and control of individual key performance indicators and total supply chain performance, and in this way, become the support to the management in strategic decision making.
Make in the different stages of the SN/CM, from the point of view of a structure Decentralized vs. Centralized (different grades). It's obviously a simplification and there are many clarifies that they have to see with the type SN/C, where they have to see his different Stages and Hierarchic Levels. In the SN/C it's difficult to detect and to transmit the Information that it finds dispersed and fragmented that goes from the Supplier of raw material up to the final consumer. For which it tries to study in depth the Methodologies of Modeling in the Hierarchical Planning of the SN/CM and in particular to propose a Preliminary Methodology for the Supply Chain Hierarchical Planning in the Uncertainty Context. More specifically, it: 1. considered decisional visions in the Hierarchical Planning of the Supply Network/Chain 2. performed a literature review of the uncertainty in the Supply Chain 3. studied sources of uncertainty along the Supply Chain 4. took into consideration models of classification for the Hierarchical Planning in the Supply Network/Chain under uncertainty 5. designed a preliminary methodology for the Hierarchical Planning of the Supply Network/Chain.