As an integral part of production planning control, order release management is critical to enhance the competitiveness and production efficiency of companies. Previous literature shows limited application of optimization-based models in assembly job shops, primarily due to the intricate nature of product structures and assembly operations. Therefore, based on the idea of the allocated clearing function (ACF) model, we introduce material flow constraints and complex assembly structure constraints during the assembly stage, proposing the assembly job shop allocated clearing function (AACF) model. The performance of the AACF model and the rule-based mechanisms in terms of cost and timing measures are compared through experiments containing 6 factors and 96 scenarios. The results show that the AACF model performs better in terms of cost management, service level and order due date deviation. In addition, a sensitivity analysis of the objective function parameters is performed to confirm the robustness of the AACF model. Finally, a case application in a real assembly shop illustrates the feasibility and validity of the proposed AACF model.

Assembly buildings, in the context of the low-carbon transformation of the construction industry, achieve superior outcomes in terms of carbon emission reduction, enhancement of building uniformity, and optimization of resource utilization as compared to traditional buildings. However, the supply chain for assembly building is marked by a significant susceptibility to risk and a need for timely fulfillment of requirements. This paper examines the risk of disruption and capacity limitations in the assembly building supply chain resulting from supply disruptions. It establishes a three-tier supply chain for assembly buildings, including primary component suppliers, backup suppliers, assembly manufacturers, and retailers. The study compares the optimal decision-making and coordination strategies of the supply chain members under centralized, decentralized, and joint agreements. The supply chain dual-source procurement decision coordination model is constructed by incorporating capacity constraints and analyzing the effects of supply disruption probability, repurchase coefficient, revenue sharing coefficient, cost, and other parameters on the expected profits of the supply chain members using arithmetic simulation. Research has indicated that when the likelihood of a disturbance occurring rises, the anticipated financial gain for the main provider decreases, while the predicted financial gain for the secondary supplier increases. The implementation of a collaborative agreement between the assembly maker and the parts backup provider would result in much greater anticipated profits compared to the decentralized decision-making approach. The impact of the revenue sharing coefficient on the predicted earnings of retailers and assembly manufacturers is more significant compared to the repurchase coefficient. The selection bias between NA and NB techniques under capacity constraints mostly arises from the assertiveness of the wholesale asking prices of inexpensive component suppliers, leading assembly manufacturers to increasingly prefer the NA option. This paper's research successfully achieves the contractual coordination of the assembly building supply chain, enhances the resilience of the assembly building supply chain, and promotes the long-term sustainable development of the assembly building supply chain.

With the organic integration of the Internet and remanufacturing industry, traditional manufacturers can recycle used products and sell products (including new and remanufactured products) through e-commerce retail platforms. A recycling and remanufacturing supply chain with three members (manufacturer, e-commerce retail platform, third-party recycler) is constructed in this paper. Manufacturer has remanufacturing capabilities, and the e-commerce retail platform can provide logistics service. In response to the organic integration of the Internet and remanufacturing industry, we mainly consider the pricing decisions of consumer preferences for online sales models and recycled products’ quality. Based on the impact of consumer used product recycling promotion activities on supply chain, a pricing game model was constructed for three recycling channels: manufacturer, e-commerce retail platform, and third-party recycler. Optimal pricing decision, logistics service level, used product recycling promotion intensity index, and recycling rate were obtained. Research has shown that consumer preferences can significantly improve supply chain logistics service level, pricing, market demand, and profits; Strengthening consumer awareness of remanufacturing used products and improving recycled products’ quality can not only lower consumer purchase prices and expand consumer demand, but also increase profits of supply chain members.

Increasing customer apprehensions regarding the security and nutritional value of agricultural goods are compelling governments and industries to implement traceable, transparent, and reputable logistics management systems. Blockchain-based agricultural logistics management systems guarantee the permanence of data once it is uploaded but cannot cope with the risk of data being falsified before uploading to the blockchain. In this work, we developed a collaborative game model between government bodies and agricultural enterprises based on the evolutionary game theory and explored the influencing factors of enterprises following the rules to share the real traceability information through numerical simulation using MATLAB. The findings show that government incentives and penalties promote positive behavior, and consumer and media supervision contribute to supply chain transparency, but firms tend to share truthful information only when it benefits them. This study builds upon existing research on the impact of social variables on both members' decision-making behavior. It highlights the positive roles of consumers and the media in the supervision of agricultural product traceability, which can help to raise public awareness of social responsibility and thus promote positive interaction in the market.

With the development of a new generation of information technology, smart elderly care plays an important role in promoting the construction of elderly care services. The emerging application tools provide door-to-door meal service for urban elderly groups, solving meal problems for special and ordinary elderly with different priority levels and penalty costs of violating time windows. Based on this, considering the personalized needs of the elderly group, this study examines the route optimization problem of cooperative delivery of elderly meals by trucks and robots, and builds a mixed integer programming model to minimize the total cost of the system. For large-scale problems, this study designs an improved adaptive large neighbourhood search algorithm that incorporates simulated annealing algorithm and artificial bee colony algorithm to avoid falling into local optimality. Experiments have proved feasibility and effectiveness of the algorithm and proposed the corresponding management insights from the aspects of delivery efficiency and service quality.

On the production side, blockchain is being widely applied to agricultural product supply chains (APSCs), which can effectively improve circulation efficiency and reduce transportation losses. On the sales side, many companies are utilizing key opinion leaders (KOLs) to promote and sell agricultural products. The combination of the two enhances the farm-to-fork transparency of agricultural products and stimulates consumer purchases. Based on these, we construct four theoretical models to study blockchain investment and livestreaming mode strategies in the APSC. The results show that investing in blockchain always stimulates consumer purchases of agricultural products, while KOL livestreaming increases consumer purchases only when the increase-traffic power is greater than a certain threshold. There is a win-win situation where the fresh product supplier (FPS) and the e-retailer can benefit from investing in blockchain and introducing KOL livestreaming, respectively. Investing in blockchain is always beneficial for the KOL, and there is free-riding behavior in the APSC. Interestingly, the enhanced increase-traffic power within a certain interval may become a negative driving force, seriously harming the FPS. In addition, we find that investing in blockchain and introducing KOL livestreaming does not always benefit consumer surplus and social welfare, which depend on the KOL’s increase-traffic power, commission rate, and unit cost.

The 531 New Deal has gradually transitioned the photovoltaic market policy from industrial policy to competition policy. This paper considers the two policy orientations of the photovoltaic supply chain: industrial policy and competition policy. Based on differential game theory, the profit models of photovoltaic supply chain entities under the two policy orientations are constructed, and the optimal solutions of each model are solved. The research finds that policy guidance factors affect the strategic choices of photovoltaic supply chain entities; Compared to industrial policies, competition policy orientation can increase the profits of various entities in the photovoltaic supply chain to varying degrees.

Blockchain technology has attracted widespread attention due to its advantages of decentralization, as well as non-tampering, transparency, and traceability of information. Fourth-party logistics systems that do not use blockchain incur transaction costs and service quality losses due to the inability to fully control the delivery process, whereas the use of blockchain eliminates the transaction costs and quality losses, but the use of blockchain needs implementation and marginal use costs. To study the conditions for the use of blockchain technology, consider the fourth-party logistics system does not use and uses blockchain technology, and the equilibrium strategies in the two cases are compared. Numerical experiments show that there exists a certain range of blockchain costs which leads to a Pareto improvement in profits for both fourth-party logistics and third-party logistics and an improvement in the quality of logistics services when using blockchain.

Robust supply chain network design that considers supply resiliency, plays vital role in supply chain risk management in dealing with various operational and disruption risks. This study developed a novel three-stage decision approach to consider two echelons robust and resilient supply chain networks. We present a mixed-integer non-linear programming model with two objective functions. The objectives are maximization of SCN profit and maximization of resiliency, where robustness, agility, leanness, flexibility, and integrity can be defined as the five resiliency criteria. Fuzzy Simultaneous Evaluation of Criteria and Alternatives (FSECA) and Simple Multi-Attribute Rating technique (SMART) have been used to obtain the supplier resiliency and weighted importance of resilience criteria. Then, a robust optimization model is built based on uncertainty parameters considering supplier resiliency. A Non-dominated Sorting Genetic Algorithm (NSGAII) and Multi Objective Particle Swarm optimization (MOPSO) were used to solve the robust model on a large scale. parameters calibrated by the Taguchi method and five metrics of performance evaluation were considered to compare the meta-heuristic algorithms. We demonstrate the proposed NSGAII algorithm over a competing method based on five performance metrics. The research findings reveal the optimal level of robust supply chain networks based on algorithm performance and Taguchi analyses. Moreover, the results indicate that when profit increases, resilience can increase simultaneously.

To meet consumer replacement needs, the free replacement extended warranty (FREW) is born and becomes popular in the extended warranty (EW) market. In this context, firms need to consider whether to introduce the FREW. Given the limited resources of the firms and cannibalism caused by the FREW, firms need to decide how to introduce the FREW. To address these issues, we construct theoretical models and obtain some managerial insights. We find that the optimal introduction strategy is related to the development cost and the expansion effect on the product market. Moreover, the optimal bundling strategy is affected by the unit maintenance cost and the cost discount caused by the FREW. Only when the benefit of the FREW is great enough, is bundling always better. An interesting result is that the price of the bundled EW is higher than the sum of the EWs’ prices when selling EWs separately.