چکیده:
در گذشته معمولاً کانال سنتی یا همان خردهفروشها برای فروش محصولات استفاده میشد؛ اما با توسعهیافتن تجارت الکترونیک، شرکتها به فکر ایجاد کانالهای فروش دیگری مانند وبسایتها افتادهاند. باتوجهبه وجود دو کانال برای فروش، انتخاب استراتژی مناسب برای قیمتگذاری اهمیت زیادی پیدا کرده است. همچنین در مبحث قیمتگذاری و برنامهریزی تولید، ریسک فاکتور بسیار مهمی است. در این مقاله از سیاست برونسپاری برای مقابله با ریسک، استفاده و مدل ریاضی جدیدی برای تصمیمگیری همزمان مباحث قیمتگذاری و برونسپاری در زنجیره تأمین سهسطحی و دوکاناله با وجود عدم قطعیت ارائه شده است. در مقاله ابتدا مدل غیرخطی برای سود زنجیره ارائه شده است؛ سپس باتوجهبه پیچیدهبودن مدل از روش فراابتکاری شبیهسازی تبرید و مدلسازی احتمالی براساس سناریو برای حل مدل پیشنهادی استفاده شده است. پارامترهای اولیۀ این الگوریتم با روش تاگوچی تنظیم میشوند. نتایج محاسباتی و تحلیل حساسیت نشاندهندۀ کارایی روش حل پیشنهادی برای حل مسئله است.
In the past, traditional channel or retailer was used for selling products but with the development of e-commerce, a large company in the world considers another sale channel like websites. Considering the existence of two channels for sale, choosing the right strategy for pricing has become important. In pricing and production planning, risk is a very important factor. In this paper, outsourcing policies have been used to deal with risks and a new mathematical model is presented for simultaneous decision-making on pricing and outsourcing in a three-level and two-channel supply chain despite uncertainty. In this paper, a nonlinear model is presented for supply chain profit function. According to the complexity of profit function, a meta-heuristic algorithm based on simulated annealing and scenario-based stochastic model are used to solve the proposed model. The initial parameters of this algorithm are set by Taguchi method. The computational results and sensitivity analysis indicate the effectiveness of the proposed solving method for problem solving. Introduction: The rapidly expanding Internet provides an opportunity for organizations to distribute their products via a direct channel, while continuing to sell their products through the traditional retail channel. Although a hybrid channel strategy provides firms with many benefits and enables them to capture a larger share of the market, combining the retail distribution channel with direct channel may pose some challenges (Chiang et al., 2003). A comprehensive review of multi-channel models can be found in Cattani et al. (2004) and Tsay and Agrawal (2004). On the other hand, the disruption in supply networks is an important supply chain risk. Natural or man-made disasters such as equipment breakdowns, labors trikes, traffic interruptions, earthquakes, floods, and hurricanes may cause supply disruptions (Chen & Xiao, 2015). In this paper, we focus on supply disruption which happened by production downtime. One of the most common policies for risk mitigation is flexible multiple-sourcing. We use both the regular production run and the outsourcing mode due to the production disruption risk and uncertainty of capacity allocation. One of the applied studies conducted on pricing and disruption management is by Huang et al. (2013) in which production costs are disrupted. Yu et al. (2009) focus on evaluating the impacts of supply disruption risks on the choice between the famous single and dual sourcing methods in a two-stage supply chain with a non-stationary and price-sensitive demand. Chen and Xiao, et al (2015) developed supply chain game models with multiple uncertainties, and outsourcing mode due to his production disruption risk and uncertainty of capacity allocation. In the literature examined, the effect of outsourcing on pricing and production planning in dual channel supply chain which is under disruption risks is not taken into account. Materials and Methods: We consider a dual channel supply chain in which a manufacturer sells to retailers as well as directly to end customers. The manufacturer sells the products to the retailer at wholesale price w. The retailer sells the products to end customers at retail price . The manufacturer sells the products to end customers directly at direct sale price . We assume that the channel demand functions in the two channels are random and linear in self-price and cross-price effects. Regular production capacity of the manufacturer is denoted by Y. We assume production is subject to a random disruption risk, and with disruption, the regular production will reach zero. The probability of disruption of production will be indicated by p . When the supply disruption occurs, the manufacturer cannot fulfill the order from the retailer. Therefore, we assume that in addition to a regular production run, the manufacturer has access to an outsourcing option with the higher procurement cost and the outsourcing production is perfectly reliable. The expected total profit for integrated dual channel supply chain is obtained as follows which comprises total revenue, production, holding, and shortage costs in both manufacturer and retailer under both disruption and non-disruption situations. Then, to simplifying the model, the problem is remodeled based on scenarios Results and Discussion: In this study, in order to achieve an optimal pricing and outsourcing, simulated annealing algorithm (SA) is developed. To get better output from SA, the initial solution is obtained from the scenario-based model which is solved by GAMS. This solution is used in SA algorithm. This method shows that the combination of SA and scenario based model in this specific way can adapt advantages of both methods. The sensitivity analysis show that with the increased sensitivity of direct channel demand or indirect channel demand to the price, the price of both channels decreases. With increasing the potential market demand, prices will rise. With increasing cost of outsourcing, prices on both channels are reduced. Conclusion: In this paper, a non-linear stochastic model for pricing and determining the amount of outsourcing in the dual channel supply chain with disruption was presented. Regarding the non-linearity and complexity of model, the simulated annealing algorithm was used to solve the model. To improve the algorithm and approaching the answer to the optimal answer, the initial response value in the algorithm was obtained using a scenario-based model used in the algorithm. References Cattani, K., Gilland, W. G., & Swaminathan, J. M. (2004). Coordinating Traditional and Internet Supply Chains. In Handbook of Quantitative Supply Chain Analysis, Modeling in the eBusiness Era, PP. 643–80. Chen, K., & Xiao, T. (2015). Outsourcing strategy and production disruption of supply chain with demand and capacity allocation uncertainties. International Journal of Production Economics, 170, 243-257. Chiang, W. Y. K., Chhajed, D., & Hess, J. D. (2003). Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design. Management science, 49(1), 1-20. Huang, S., Yang, C., & Liu, H. (2013). Pricing and production decisions in a dual-channel supply chain when production costs are disrupted. Economic Modelling, 30, 521-538. Tsay, A. A., & Agrawal, N. (2004). Modeling conflict and coordination in multi-channel distribution systems: A review. In Handbook of quantitative supply chain analysis (pp. 557-606). Springer, Boston, MA. Yu, H., Zeng, A. Z., & Zhao, L. (2009). Single or dual sourcing: decision-making in the presence of supply chain disruption risks. Omega, 37(4), 788-800.