Asia-Pacific Journal of Operational Research

Radio frequency identification technology has been applied in many fields, especially in logistics operations and supply chain management. Supply chain coordination among partners, which is the core part of supply chain management, can be more practical and effective through sharing real-time product data along the supply chain tracked by RFID technology. This paper focused on the study of the supply chain collaborative forecasting process by sharing RFID real-time data. The collaborative forecasting process among supply chain partners based on the sharing RFID product data is discussed for product demand decision in the paper at first. Then, a Stein-rule combination-forecasting model is proposed to integrate the forecasting knowledge and coordinate forecasting process between the retailers and manufactures shared the RFID data in the supply chain. Moreover, in order to enhance collaborative forecasting precision an error correction combination-forecasting model is discussed. Finally, the outcomes of mathematics simulation verify that the forecast combinations with Stein-rule estimation rules and error correction algorithms are effective to improve forecast precision and coordinate RFID-based supply chain.

In this paper, we design a revenue share contract when a supplier is the leader and a retailer is the follower in a two-echelon supply chain. The innovation lies in dividing the supplier’s marketing strategies into two types: the profit oriented and the sales oriented to distinguish the different decision objectives from previous literatures assuming the supplier and retailer are both profit oriented. The paper uses the revenue share contract to reach supply chain coordination and Pareto optimality in the supply chain with the profit-oriented suppliers. However, the contract makes supply chain collaboration solutions and the Pareto improvement with the sales oriented supplier conditional. Numerical examples are given to illustrate these cases.

In this paper, we develop a logistics service supply chain network equilibrium model in which four tiers of decision makers (logistics service subcontractors (LSS), logistics service providers (LSP), logistics services integrators (LSI) and logistics service demand sides (LSD)) seek to determine their respective optimal conditions, with the LSI holding a leading position. We model the optimizing behavior of decision-makers, with the LSI being multicriteria decision-makers which are concerned with both profit maximization and risk minimization. We derive the equilibrium conditions and establish the finite-dimensional variational inequality (VI) formulation. A new smoothing self-adaptive L-M algorithm is established to solve this problems. Finally, we illustrate the effectiveness and feasibility of the model by an example.

Dual-channel supply chain system, channel optimization is influenced by channel attitude toward risk, in which risk is classified as general risk and interruption risk. To consider lead time may bring out supply conflicts, substitution effect of online channel and ratio of promotional cost are introduced and an independent model is developed. Based on that, the impact of interruption risk under risk-aversion attitude on both channels is further studied. Finally, it is proved how the risk attitude influences pricing and profit strategy.

Due to double marginalization effect, the wholesale price contract has been proved that it cannot coordinate a decentralized supply chain (DSC) based on the framework of Stackelberg game, in which the upstream firm acts as a leader and the downstream firm acts as a follower. Nevertheless, it has shown that the partnership between the enterprises tends to be equality. Motivated by this factor, this paper studies the coordination of wholesale price contract under the perspective of equality between enterprises. First, an innovative wholesale price contract is constructed and to prove that the constructed contract can flexibly coordinate the DSC. Second, the adaptability of the constructed contract is analyzed and compared with the revenue sharing contract, which is designed under the framework of Stackelberg game. Third, numerical analysis is calculated to verify the effectiveness and operation of the model.

The split delivery vehicle routing problem (SDVRP) is a variation of the capacitated vehicle routing problem in which some customers may be served by more than one vehicle. We have proposed a particle swarm optimization approach that incorporates a local search to solve the SDVRP. An integer coding method was presented, and a decoding method based on Bellman’s equation was modified for the SDVRP. A way to address the differences in the length of the velocity vector, the position vector, the personal best position vector, the local best position vector and the global best position vector was designed. Two groups of local searches for top solutions were incorporated into the algorithm, with the ability to control whether they are executed on a given solution. The algorithm was initially tested using the modified Solomon’s instances to verify the parameters used, including the local search probability, the size of the swarm, the velocity equation and the length of the vectors. Extensive computational experiments were carried out on 131 benchmark instances available in the literature. The results obtained were competitive. More precisely, equally good solutions were found in 32 instances, and improved solutions were found in 35 instances, with an average improvement of 0.02% and a maximum improvement of 1.12%.

Online-to-offline (O2O) business model is the new online shopping model in which consumers purchase products or services online and get the products or services in offline physical store. Online subsidies service which provides subsidies for online order is the common way adopted by O2O business to expand the market demand. The demand changes brought by online subsidies service will temporarily disrupt the supply chain balance. In this paper, the O2O supply chain with online subsidies service is modeled to analyze the influence of demand disruption on O2O supply chain performance at the beginning. Then, the optimization of O2O supply chain with online subsidies service to face demand disruption is discussed.

This paper addresses the operational decisions and coordination of the supply chain in the presence of risk aversion, where the risk averse retailer’s performance is measured by a combination of the expected profit and conditional value-at-risk (CVaR). Such performance measure reflects the desire of the retailer to maximize the expected profit on one hand and to control the downside risk of the profit on the other hand. The impact of risk aversion on the supply chain’s decision and performance is also explored. To overcome the inefficiency due to the double marginalization and the aggravation resulting from risk aversion, we investigate the buy-back contract to coordinate the supply chain. Such contract can largely increase the supply chain’s profit, especially when the retailer is more risk averse. Lastly, we extend such risk measure to the widely-used business model nowadays — platform selling model, and explore the impact of the allocation rule on the manufacturer’s decision.