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In the supply chain environment, agile distribution refined the division of operations, responded quickly to the customer needs of the mobile terminal, and promoted the construction of an intelligent logistics distribution system. In order to integrate the distribution resources of the distribution system of the logistics industry and maximize the overall benefits of distribution, this paper designs an intelligent logistics agile distribution model and optimizes the distribution strategy. Firstly, this paper puts forward a rationalization evaluation system based on the established logistics agile distribution model. Make full use of the fuzzy subsets of each level to quantify the fuzzy indexes to evaluate, and then comprehensively clarify the index attributes through the fuzzy transformation criteria to obtain the evaluation results. Secondly, aiming at the networked agile distribution organization form, the scientific location mathematical model of agile distribution center and the path mathematical model of the agile distribution are established. Finally, the uncertain influence of many objective conditions on distribution agility has been analyzed, and the dynamic optimization model of an agile distribution path with the concept of time window under random demand is constructed. Through the experimental analysis, the rationalization evaluation strategy and index of verification test results show that the model has significant optimization advantages, which not only improve the rationality and economic benefits of distribution, but also meet the time requirements of all users. [ABSTRACT FROM AUTHOR]

To improve the efficiency of warehouse operations, reasonable optimization of picking operations has become an important task of the modern supply chain. For the purpose of optimization of order picking in warehouses, a new fruit fly optimization algorithm, particle swarm optimization, random weight, and weight decrease model are used to solve the mathematical model. Further optimization is achieved through the analysis of the warehouse shelves and screening of the optimal solution of the picking time. In addition, simulation experiments are conducted in the MATLAB environment through programming. The shortest picking time is found out and chosen as an optimized method by taking advantage of the effectiveness of these six algorithms in the picking optimization and comparing the data obtained under the simulation. The result shows that the optimization capacity of RWFOA is better and the picking efficiency is the best. [ABSTRACT FROM AUTHOR]

This paper explores the quantity discount coordination models in the fashion supply chain with uncertain yields and random demand. The paper proves that, under the independent and noncoordinated decision patterns, there exists a Nash equilibrium between the supplier and the manufacturer which reduces the supply chain's profit margin. In order to achieve the "optimal" centralized supply chain expected profit margin, new quantity discount models have been established. Both the supplier-oriented and the manufacturer-oriented Stackelberg supply chain gaming models are investigated. Our analytical and numerical analyses show that the quantity discount contract proposed in this paper can largely reduce the negative influence brought by the uncertainty of yields and demand. Therefore, the profit margin of supply chains based on quantity discount can reach the optimal level of the supply chain under the centralized setting. [ABSTRACT FROM AUTHOR]

In consideration of influence of loss, freshness, and secret retailer cost of products, how to handle emergency events during three-level supply chain is researched when market need is presumed to be a nonlinear function with retail price in fresh agricultural product market. Centralized and decentralized supply chain coordination models are studied based on asymmetric information. Optimal strategy of supply chain in dealing with retail price perturbation is caused by emergency events. The research reveals robustness for optimal production planning, wholesale price for distributors, wholesale price for retailers, and retail price of three-level supply chain about fresh agricultural products. The above four factors can keep constant within a certain perturbation of expectation costs for retailers because of emergency events; the conclusions are verified by numerical simulation. This paper also can be used for reference to the other related studies in how to coordinate the supply chain under asymmetric and punctual researches information response to disruptions. [ABSTRACT FROM AUTHOR]

There is a rising trend in supplying chain management to employ simultaneous cooperation and competition (coopetition) among supply chain partners as an efficient strategy to create value. There exist, however, few models which analyze coopetitive situations mathematically. Cooperative game theory is the common tool in analyzing cooperative situations. However, the term "cooperative" in "cooperative game theory" is absolutely misleading since it ultimately leads to competition analysis and ignores the internal structure of the cooperation. Coopetition, however, results in structural transformations in players. Therefore, we require a mathematical modeling approach which takes into account the internal structural changes due to cooperation among competitors. In so doing, in this paper we propose, we assume that those parameters of each firm's profit function are subject to transformation by cooperation as a function of cooperation level so as to determine the right level of cooperation and production of firms while considering technical cooperation between them. Furthermore, we demonstrate the results of applying the idea to a supply chain situation where two similar suppliers participate. We conclude that under intuitive conditions coopetition strategy is superior to the pure competitive relationship between the suppliers in terms of profitability which validates the previous empirical results mathematically. [ABSTRACT FROM AUTHOR]

This paper considers a two-level supply chain coordination problem for fixed lifetime products with permissible delay in payments. Two cases are discussed; that is, the retailer is required to settle the balance before the end of the ordering cycle (Case I) and after the ordering cycle (Case II). The coordination models are proposed and analyzed, respectively. The analytical methods as to how to determine the optimal policy are presented. In addition, it is indicated that the supplier's cost as well as that of the total system will be reduced no matter how much the parameters change, and the retailer will benefit from coordination, if the supplier is willing to share the cost saving with him/her in Case I. In Case II, the retailer's average cost will be reduced and the supplier will benefit from coordination only under certain conditions. Besides, the results show that, for fixed lifetime products, providing longer credit period than the retailer's order period is not commonly applicable. [ABSTRACT FROM AUTHOR]

Nowadays, a trend of forming dynamic supply chains with different trading partners over different e-marketplaces has emerged. These supply chains, which are called "supply mesh," generally refer to heterogeneous electronic marketplaces in which dynamic supply chains, as per project (often make-to-order), are formed across different parties. Conceptually, in a supply mesh a dynamic supply chain is formed vertically, mediating several companies for a project. Companies that are on the same level horizontally are either competitors or cohorts. A complex scenario such as this makes it challenging to find the right group of members for a dynamic supply chain. Earlier on, a multiagent model called the collaborative single machine earliness/tardiness (CSET) model was proposed for the optimal formation of make-to-order supply chains. This paper contributes the particular agent designs, for enabling the mediation of CSET in a supply mesh, and the possibilities are discussed. It is demonstrated via a computer simulation, based on samples from the U.S. textile industry, that by using intelligent agents under the CSET model it is possible to automatically find an ideal group of trading partners from a supply mesh. [ABSTRACT FROM AUTHOR]

In this paper, the competition between two supply chains and their corresponding elements is modeled following the evolutionary games approach. Each of the supply chains consists of a supplier and a manufacturer. Customers are of one type and are sensitive to price and delivery time and receive identical services from the two supply chains. One of the chains acts traditionally (TSC) in a monopoly market until the other chain enters the market acting electronically (ESC) and changes the market to a duopoly. This competition continues as evolutionary game until equilibrium is reached in the market. Mathematical models for analyzing internal and external competition issues are developed under four different scenarios: (i) both chains choose intercorporate strategy for their elements; (ii) the first chain chooses intercorporate strategy while the second one chooses intercompetition strategy for their elements; (iii) the first chain chooses intercompetition strategy and the second one chooses intercorporate strategy for their elements; (iv) both chains choose intercompetition strategy for their elements. The best policies for TSC and ESC are found assuming identical conditions and furthermore in steady statewhen equilibriumis reached in the market, the best price and delivery time policy of chains is illustrated by numerical example. [ABSTRACT FROM AUTHOR]