Design of Trade Promotion to Maximize Overall Supply Chain Profitability using Mathematical Optimization

Author(s):  
Ashwini Bambal ◽  
Sunil Kumar ◽  
Jibi Abraham
Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Daniel Arturo Olivares Vera ◽  
Elias Olivares-Benitez ◽  
Eleazar Puente Rivera ◽  
Mónica López-Campos ◽  
Pablo A. Miranda

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.


2016 ◽  
Vol 19 (3) ◽  
pp. 721-734 ◽  
Author(s):  
Manuel Alejandro Méndez-Vázquez ◽  
Fernando Israel Gómez-Castro ◽  
José María Ponce-Ortega ◽  
Alma Hortensia Serafín-Muñoz ◽  
José Ezequiel Santibañez-Aguilar ◽  
...  

Author(s):  
Eduardo dos Santos Teixeira ◽  
Socorro Rangel ◽  
Helenice de O. Florentino ◽  
Silvio Alexandre de Araujo

Author(s):  
Yu-Chung Tsao ◽  
Hui-Ling Fan ◽  
Lu-Wen Liao ◽  
Thuy-Linh Vu ◽  
Pei-Ling Lee

This research develops two models to consider retailer sales promotion and manufacturer trade promotion under demand uncertainty. The objective of the first model is to determine the retailer’s optimal promotional effort and order quantity while maximizing the retailer’s profit under exogenous trade promotion. The second model extends the first to consider the manufacturer’s endogenous trade promotion decisions. For these models, three different trade promotion policies (off-invoice, scan-back, unsold-discount) have been compared to identify the policy that can increase the manufacturer’s and the retailer’s profits. For the model with exogenous trade promotion, the retailer’s promotional effort level, order quantity, and profit are highest under the off-invoice trade promotion policy. With respect to the manufacturer’s endogenous trade promotion decisions, the retailer’s promotional effort level, order quantity, and profit, and the manufacturer’s profit are higher under the off-invoice policy than under the scan-backs policy. When comparing the three different trade promotion policies, we also find that the wholesale price is a key factor that influences a manufacturer’s profit. Our research sheds light on the importance of trade promotion policy in supply chain management.


2020 ◽  
Author(s):  
Philip Tominac ◽  
Horacio Aguirre-Villegas ◽  
Joseph Sanford ◽  
Rebecca A. Larson ◽  
Victor Zavala

<p>We apply systems engineering principals and life cycle analysis (LCA) to municipal waste supply chains to elucidate sustainability incentives. Environmental impacts are quantified using LCA for waste management technologies available in the supply chain, and included as products. The supply chain is modeled as a coordinated market and resolved using mathematical optimization techniques. Incorporating impacts as products allows us to analyze the influence of tax policy on optimal waste management strategies.</p>


Author(s):  
Hisashi Kurata ◽  
Xiaohang Yue ◽  
Layth C. Alwan

Trade promotion has a significant impact on the fashion retail business. Manufacturers have traditionally been concerned with the inefficient trade promotion due to the low pass-through rate of the trade deals from retailers to customers. The scan-back (SB) trade deal, which monitors a retailer’s sales via an IT system, benefits the manufacturer, but may or may not benefit the retailer. We provide insight into when a retailer has incentive to accept the SB trade deal. We show that (1) the manufacturer and the entire supply chain can always benefit from the SB trade deal while the retailer benefits only under some conditions, and that (2) both the retailer and the manufacturer can benefit from the SB trade deal if the SB deal is accompanied by a buyback contract. We examine the effect of a retailer’s confidential pass-through rate on a firm’s incentive to use the SB trade deal.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
R. Ghasemy Yaghin ◽  
P. Sarlak

PurposeThis paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon emission in textile production and transportation is considered along with supply chain profitability.Design/methodology/approachThe authors present a fuzzy multi-objective mathematical optimization model with credibilistic chance constraints to determine the fabric procurement quantities and production plan under uncertainty. The solution procedure makes use of credibility measure and fuzzy aggregation operator to attain compromise solutions.FindingsA trade-off among carbon emissions, social performance and supply chain total profit is conducted. The analyses indicate the importance of transportation costs and carbon emission while determining the supply chain's tactical plan.Originality/valueThe textile supply chain's social sustainability alongside carbon emissions of textile operations is contemplated to provide apparel production and distribution logistics planning under uncertainty. In doing so, the authors propose a hybrid credibility-possibility mathematical optimization model to determine a compromise solution for textile managers.


Kybernetes ◽  
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hanieh Shambayati ◽  
Mohsen Shafiei Nikabadi ◽  
Seyed Mohammad Ali Khatami Firouzabadi ◽  
Mohammad Rahmanimanesh ◽  
Sara Saberi

PurposeSupply chains (SCs) have been growingly virtualized in response to the market challenges and opportunities that are presented by new and cost-effective internet-based technologies today. This paper designed a virtual closed-loop supply chain (VCLSC) network based on multiperiod, multiproduct and by using the Internet of Things (IoT). The purpose of the paper is the optimization of the VCLSC network.Design/methodology/approachThe proposed model considers the maximization of profit. For this purpose, costs related to virtualization such as security, energy consumption, recall and IoT facilities along with the usual costs of the SC are considered in the model. Due to real-world demand fluctuations, in this model, demand is considered fuzzy. Finally, the problem is solved using the Grey Wolf algorithm and Firefly algorithm. A numerical example and sensitivity analysis on the main parameters of the model are used to describe the importance and applicability of the developed model.FindingsThe findings showed that the Firefly algorithm performed better and identified more profit for the SC in each period. Also, the results of the sensitivity analysis using the IoT in a VCLSC showed that the profit of the virtual supply chain (VSC) is higher compared to not using IoT due to tracking defective parts and identifying reversible products. In proposed model, chain members can help improve chain operations by tracking raw materials and products, delivering products faster and with higher quality to customers, bringing a new level of SC efficiency to industries. As a result, VSCs can be controlled, programmed and optimized remotely over the Internet based on virtual objects rather than direct observation.Originality/valueThere are limited researches on designing and optimizing the VCLSC network. This study is one of the first studies that optimize the VSC networks considering minimization of virtual costs and maximization of profits. In most researches, the theory of VSC and its advantages have been described, while in this research, mathematical optimization and modeling of the VSC have been done, and it has been tried to apply SC virtualization using the IoT. Considering virtual costs in VSC optimization is another originality of this research. Also, considering the uncertainty in the SC brings the issue closer to the real world. In this study, virtualization costs including security, recall and energy consumption in SC optimization are considered.HighlightsInvestigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).


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