Simulation tool of supply chain model with various structure and decision making processes

2003 ◽  
Author(s):  
T. Maruta ◽  
Y. Ikkai ◽  
N. Komoda
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Chain Model ◽  
Simulation Tool ◽  
Supply Chain Model ◽  
Decision Making Processes

Decision-Making Coordination within Three-Echelon Supply Chains

2011 ◽  
pp. 93-107
Author(s):  
Jairo R. Montoya-Torres
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Process Simulation ◽  
Simulation Models ◽  
Chain Model ◽  
Total System ◽  
Direct Relation ◽  
Supply Chain Model ◽  
Brownian Process ◽  
The Impact

Supply chain performance is highly influenced by the coordination level between its members, which needs information sharing. In this paper we consider a three-echelon direct sell supply chain model and focus on the problem of coordinated decision-making between its members. Our contribution is a first approach that measures the impact of the degree of coordination between the members. Demand behavior is modeled using a geometric Brownian process. Simulation models are run in order to analyze various cooperation scenarios. Our results show a direct relation between the degree of coordination within the supply chain and the total system cost. Although this result is intuitive, our simulations allowed us to quantify such a relation and in which measure these costs are whether or not associated to imperfect coordination.

Multi-Echelon Supply Chain Modeling With Dynamic Continuous Review Inventory Policy

2012 ◽  
pp. 1505-1521
Author(s):  
K. Narayana Rao ◽  
K. Venkata Subbaiah
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Goal Programming ◽  
Chain Model ◽  
Continuous Review ◽  
Fuzzy Environment ◽  
Supply Chain Model ◽  
Fuzzy Goal ◽  
Supply Chain Modeling ◽  
Continuous Review Policy

In this chapter, an integrated procurement, production and distribution supply chain model is developed in fuzzy environment and performance vector of the supply chain is determined by solving strategic model and tactical model iteratively. Mixed integer programming model is formulated through fuzzy goal programming approach in strategic level. In the tactical level, dynamic continuous review inventory policy for controlling of raw material inventory at supplier echelon, finished products at plant echelon and distribution center echelons is assumed. The inventory models are solved by considering the interdependency of economic order quantity and reorder point. The supply chain model, which is developed in fuzzy environment, finds compromise solution with multiple, vague and in-compatible objectives. Fuzzy goal programming techniques provide feasible solutions with flexible model formulation in decision-making problems, which involve human judgments in decision-making. Need for supply chin modeling with dynamic continuous review policy in fuzzy environment and the existing literature are outlined in Introduction. Fuzzy supply chain modeling with dynamic continuous review policy for controlling of the raw materials, finished products at plant and distribution center echelons is described in Fuzzy supply chain modeling section. Flow chart of the methodology is explained in Solution Methodology section. The proposed model is illustrated through a numerical example. Supply chain cost, Volume flexibility and unit costs are determined and presented in Results and Discussion section. Importance of the methodology and future scope is made in Conclusion section. This model finds application in the industries involving continuous production like oil and natural gas, steel manufacturing industries etc

Multi-Echelon Supply Chain Modeling With Dynamic Continuous Review Inventory Policy

2011 ◽  
pp. 146-167
Author(s):  
K. Narayana Rao ◽  
K. Venkata Subbaiah
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Goal Programming ◽  
Chain Model ◽  
Continuous Review ◽  
Fuzzy Environment ◽  
Supply Chain Model ◽  
Fuzzy Goal ◽  
Supply Chain Modeling ◽  
Continuous Review Policy

In this chapter, an integrated procurement, production and distribution supply chain model is developed in fuzzy environment and performance vector of the supply chain is determined by solving strategic model and tactical model iteratively. Mixed integer programming model is formulated through fuzzy goal programming approach in strategic level. In the tactical level, dynamic continuous review inventory policy for controlling of raw material inventory at supplier echelon, finished products at plant echelon and distribution center echelons is assumed. The inventory models are solved by considering the interdependency of economic order quantity and reorder point. The supply chain model, which is developed in fuzzy environment, finds compromise solution with multiple, vague and in-compatible objectives. Fuzzy goal programming techniques provide feasible solutions with flexible model formulation in decision-making problems, which involve human judgments in decision-making. Need for supply chin modeling with dynamic continuous review policy in fuzzy environment and the existing literature are outlined in Introduction. Fuzzy supply chain modeling with dynamic continuous review policy for controlling of the raw materials, finished products at plant and distribution center echelons is described in Fuzzy supply chain modeling section. Flow chart of the methodology is explained in Solution Methodology section. The proposed model is illustrated through a numerical example. Supply chain cost, Volume flexibility and unit costs are determined and presented in Results and Discussion section. Importance of the methodology and future scope is made in Conclusion section. This model finds application in the industries involving continuous production like oil and natural gas, steel manufacturing industries etc

Coordination and competition in two-echelon supply chain using grey revenue-sharing contracts

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ayad Hendalianpour ◽  
Mohammad Hamzehlou ◽  
Mohammad Reza Feylizadeh ◽  
Naiming Xie ◽  
Mohammad Hossein Shakerizadeh
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
High Performance ◽  
Wholesale Price ◽  
Revenue Sharing ◽  
Chain Model ◽  
Selling Price ◽  
Quantity Discount ◽  
Content Type ◽  
Supply Chain Model

PurposeThis study examines the potential of contracts as one of the supply chain coordination mechanisms under competitive conditions. It also investigates a two-echelon supply chain model with two manufacturers and two retailers to develop a competitive structure in grey stochastic demand.Design/methodology/approachSupply chain demand is considered as a stochastic phenomenon depending on the selling price of the product. Also, products can be replaced by market manufacturers. Each retailer faces the pricing of products from two manufacturers, leading to competition between downstream retailers. In the present study, the duopoly supply chain model was presented based on the wholesale price contract, revenue-sharing contract and quantity discount contract separately.FindingsGrey optimization and analysis of their coordination were presented. The results showed the high performance of revenue-sharing contracts in the supply chain. Thus, manufacturers will give the next priority to quantity discount contracts.Originality/valueOrdering is the main factor contributing to competitive decision-making. Meanwhile, decision-making along with ordering and pricing will be required due to the nature of the demand.

Two-echelon imperfect production fuzzy supply chain model for reliability dependent demand with probabilistic deterioration and rework

2021 ◽  
pp. 1-15
Author(s):  
Sudip Adak ◽  
G.S. Mahapatra
Keyword(s):  
Supply Chain ◽  
Production Rate ◽  
Production Cost ◽  
Idle Time ◽  
Chain Model ◽  
Specific Time ◽  
Defective Items ◽  
Imperfect Production ◽  
Supply Chain Model ◽  
Dependent Demand

This paper develops a fuzzy two-layer supply chain for manufacturer and retailer with defective and non-defective types of products. The manufacturer produces up to a specific time, including faulty and non-defective items, and after the screening, the non-defective item sends to the retailer. The retailer’s strategy is to do the screening of items received from the manufacturer; subsequently, the perfect quality items are used to fulfill the customer’s demand, and the defective items are reworked. The retailer considers that customer demand is time and reliability dependent. The supply chain considers probabilistic deterioration for the manufacturer and retailers along with the strategies such as production rate, unit production cost, cost of idle time of manufacturer, screening, rework, etc. The optimum average profit of the integrated model is evaluated for both the cases crisp and fuzzy environments. Managerial insights and the effect of changes in the parameters’ values on the optimal inventory policy under fuzziness are presented.

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