Multi-echelon Supply Chain Optimization: Methods and Application Examples

Author(s):  
Marco Laumanns ◽  
Stefan Woerner
Author(s):  
Dileep M V ◽  
◽  
Dr. Regi Kumar V ◽  

Customer satisfaction is the backbone of any business entity and supply chain optimization plays a vital role in customer satisfaction efforts. Supply chain inventory control is one of the scientific supply chain optimization methods for determining proper inventory levels at different stages or echelons of the supply chain to meet the requirements of the customers. The intention is to supply right type of material at exact time in appropriate quantities and at competitive rates. Supply chain inventory costs consist of costs to store, track and insure materials. Inventories that mishandled create substantial financial problems for a business, whether the mismanagement results in an inventory accumulation or an inventory shortage. Therefore, an examination of the right quantities to be kept in stock to meet the requirements, the strategic location, storage facilities and recordings of the goods or items should be done systematically such that the desired degree of service can be provided at competitive prices or at minimum ultimate cost. Major objective of inventory control in a multi echelon supply chain is to optimize inventory cost elements like transportation cost, carrying cost, holding cost and all other inventory related costs at all supply chain stages with an elevated service level at the end customer point. The supply chain inventory control becomes tough when the handling material is a perishable one as its deterioration rate is variable rather than constant. This article provides the study results of the deterioration rate of a perishable edible inventory at different selected environmental conditions. The focus of this article is to introduce a mathematical equation for the deterioration rate of the selected perishable inventory which is inevitable for the formulation of inventory models for its supply chain echelons.


2005 ◽  
Vol 29 (6) ◽  
pp. 1305-1316 ◽  
Author(s):  
E.P. Schulz ◽  
M.S. Diaz ◽  
J.A. Bandoni

2015 ◽  
Vol 183 ◽  
pp. 291-307 ◽  
Author(s):  
Niklas von der Assen ◽  
André Sternberg ◽  
Arne Kätelhön ◽  
André Bardow

Potential environmental benefits have been identified for the utilization of carbon dioxide (CO2) as a feedstock for polyurethanes (PUR). CO2 can be utilized in the PUR supply chain in a wide variety of ways ranging from direct CO2 utilization for polyols as a PUR precursor, to indirect CO2 utilization for basic chemicals in the PUR supply chain. In this paper, we present a systematic exploration and environmental evaluation of all direct and indirect CO2 utilization options for flexible and rigid PUR foams. The analysis is based on an LCA-based PUR supply chain optimization model using linear programming to identify PUR production with minimal environmental impacts. The direct utilization of CO2 for polyols allows for large specific impact reductions of up to 4 kg CO2-eq. and 2 kg oil-eq. per kg CO2 utilized, but the amounts of CO2 that can be utilized are limited to 0.30 kg CO2 per kg PUR. The amount of CO2 utilized can be increased to up to 1.7 kg CO2 per kg PUR by indirect CO2 utilization in the PUR supply chain. Indirect CO2 utilization requires hydrogen (H2). The environmental impacts of H2 production strongly affect the impact of indirect CO2 utilization in PUR. To achieve optimal environmental performance under the current fossil-based H2 generation, PUR production can only utilize much less CO2 than theoretically possible. Thus, utilizing as much CO2 in the PUR supply chain as possible is not always environmentally optimal. Clean H2 production is required to exploit the full CO2 utilization potential for environmental impact reduction in PUR production.


Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Ágota Bányai ◽  
Tamás Bányai ◽  
Béla Illés

The globalization of economy and market led to increased networking in the field of manufacturing and services. These manufacturing and service processes including supply chain became more and more complex. The supply chain includes in many cases consignment stores. The design and operation of these complex supply chain processes can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on metaheuristic algorithms. This research proposes an integrated supply model based on consignment stores. After a careful literature review, this paper introduces a mathematical model to formulate the problem of consignment-store-based supply chain optimization. The integrated model includes facility location and assignment problems to be solved. Next, an enhanced black hole algorithm dealing with multiobjective supply chain model is presented. The sensitivity analysis of the heuristic black hole optimization method is also described to check the efficiency of new operators to increase the convergence of the algorithm. Numerical results with different datasets demonstrate how the proposed model supports the efficiency, flexibility, and reliability of the consignment-store-based supply chain.


2019 ◽  
Vol 121 ◽  
pp. 338-353 ◽  
Author(s):  
Yousef Saif ◽  
Muhammad Rizwan ◽  
Ali Almansoori ◽  
Ali Elkamel

2017 ◽  
Vol 15 (2) ◽  
pp. 124-139
Author(s):  
Thokozani Patmond Mbhele

The cascading order variability from downstream trumping up the upstream site of the supply chain network indicates the deleterious effect to the performance of the fast moving consumer goods industry. The fundamental likelihood to optimization in this industry requires dexterous flows of quasi-real-time information, as well as reliable product availability. In this context, this study analyzes the challenges of bullwhip effect on the perspective of ingenious optimization strategies, and further contemplates to establish the engineering patterns of interrelationships on the magnitude of pooling the resources to advance supply chain capabilities. The suppression of bullwhip effect on underlying optimization strategies is sought to elevate accelerated responsiveness, improve network demand visibility and reduce volatility in frequencies to inventory replenishment. A rigorous and disciplined quantitative approach afforded the tentatively development of pattern of interrelated supply chain dimensions. The factor analysis method was used on 448 responses and insightful findings were produced from the compelling purposive sampling technique. The findings indicate that the magnitude of better ameliorating bullwhip effect, the value of competitive economic information and strength of selected optimization strategies depend on the model of unified engineering patterns. This paper provides insights to FMCG industry on using innovative strategies and modern technology to enhance supply chain visibility through integrated systems networks.


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