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The growing concern for sustainability has forced the researchers and managers to incorporate the environmental and social factors along with the economical factors in the design of supply chains. This paper presents the design and optimization of a multi-objective closed-loop supply chain considering the economical and environmental factors with uncertainty in parameters. The proposed network is modeled as fuzzy multi-objective mixed integer linear programming problem considering multi-customer zones, multi-collection centers, multi-disassembly centers, multi-refurbishing centers, multi-external suppliers, and different product recovery processes; to take care for purchasing cost, transportation cost, processing cost, set-up cost, and capacity constraints simultaneously. The model is solved using an interactive ε -constraint method. A case example is solved using LINGO 14.0 to demonstrate the significance and applicability of the developed fuzzy optimization model for closed-loop supply chain.

Fast fashion is a timely, influential and well observed business strategy in the fashion retail industry. An effective fast fashion supply chain relies on quick and competent forecasts of highly volatile demand that involves multiple stock keeping units. However, there are multiple sources of uncertainty, such as market situation and rapid changes of the fashion trends, which makes demand forecasting more challenging. Therefore, it is crucial for the fast fashion companies to carefully select the right forecasting models to thrive and to succeed in this ever changing business environment. In this study, we first review a selected set of computational models which can be applied for fast fashion demand forecasting. We then perform a real sale data based computation analysis and discuss the strengths and weaknesses of these versatile models. Finally, we conduct a survey to learn about the perceived importance of different demand forecasting systems’ features from the fashion industry. Finally, we rank the fast fashion demand forecasting systems using the AHP analysis and supplement with important insights on the preferences on the demand forecasting systems of different groups of fashion industry experts and supply chain practitioners.

As the demands of some important products such as oil, gas, and agricultural commodities are disrupted, the government often regulates the retail price that includes impositions of a price ceiling and a price floor. In this paper, we analyze the coordination of a supply chain with a dominate retailer under the government price regulation policy by a revenue sharing contract after demand disruption. First, we characterize the optimal decisions of the supply chain under normal circumstance by the revenue sharing contract as a benchmark. Then, when the demand is disrupted, we redesign the contract to coordinate the supply chain and obtain the corresponding revenue sharing contract in different scenarios. Finally, we give some numerical examples to illustrate our theoretical results and explore the impacts of government price regulations on the coordination mechanism.

This paper investigates the coordination issue of a two-echelon fuzzy closed-loop supply chain. Two coordinating models with symmetric and asymmetric information about retailer’s collecting scale parameter are established by using game theory, and the corresponding analytical solutions are obtained. Theoretical analysis and numerical example show that the maximal expected profits of the fuzzy closed-loop supply chain in two coordination situations are equal to that in the centralized decision case and greater than that in the decentralized decision scenario. Furthermore, under asymmetric information contract, the maximal expected profit obtained by the low-collecting-scale-level retailer is higher than that under symmetric information contract.

Usually, the profit of companies will increase if they employ trade credit financing policy to encourage customer to purchase more. This paper develops a model for pricing and inventory control of non-instantaneous deteriorating items under two-echelon trade credit in which the vendor provides a credit period to the retailer and the retailer in turn offers a delay in payment to his/her customer. The price-dependent probabilistic demand function and partially backlogged shortages are adopted. Also, deterioration is shown by three different probability distribution function including (1) uniform distribution, (2) triangular distribution, and (3) beta distribution. The theoretical results are designed to determine the optimal selling price and the optimal inventory control variables so that the retailer’s total profit is maximized. Also, the necessary and sufficient conditions to prove the existence and uniqueness of the optimal solution are provided. Moreover, an algorithm is extended to describe the solution procedure. Numerical example, sensitivity analysis, and a simulation approach are presented to illustrate the performance of the algorithm and the theoretical results. Several managerial insights are also driven from computational results. The results indicate that the retailer’s total profit increases by considering the non-instantaneous deteriorating phenomenon and the trade credit policy.

This paper develops an integrated model for analyzing and designing structured supply contracts from the perspectives of the buyer, the supplier, and the entire supply chain in an open supply chain. We first present a flexible framework that encapsulates a wide range of contracting types that have been studied previously. We then introduce the concept of relative contract value vis-a-vis a reference alternative, which facilitates addressing explicitly both the demand uncertainty and the price uncertainty within which real supply relationships operate. To guide practitioners in designing optimal supply contracts, we derive closed-form expressions for optimal contract structure, quantity commitment and flexibility, pricing, and sharing policy as well as the conditions to maximize total supply chain profitability associated with a contract. Our research demonstrates that structured contracts consisting of several fixed and/or flexible components are capable of maximizing total supply chain profit and allocating profit between contracting parties arbitrarily.