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In cold chain logistics, fresh agricultural products are susceptible to deteriorate due to the passage of time in the distribution process. To reduce the loss of cargo, this research integrates the traditional refrigeration cost into the freshness-keeping cost invested in the process of transportation and unloading goods. We rely on the investment of freshness-keeping cost to reduce the cargo damage cost caused by the distribution process and then propose a new vehicle routing problem (VRP). According to all relevant costs, this research builds a mathematical model with the goal of minimizing the total distribution cost. A hybrid ant colony optimization is designed to solve the problem, and the effectiveness of the model and algorithm are verified through two sets of comparative experiments. To determine which products should be invested in freshness-keeping cost to reduce the total distribution cost, we perform numerical analysis on the relevant parameters in the model. Results provide decision-making references for cold chain logistics distribution enterprises in the design of distribution routes.
Shenjun Zhu; Hongming Fu; Yanhui Li. Optimization Research on Vehicle Routing for Fresh Agricultural Products Based on the Investment of Freshness-Keeping Cost in the Distribution Process. Sustainability 2021, 13, 8110 .
AMA StyleShenjun Zhu, Hongming Fu, Yanhui Li. Optimization Research on Vehicle Routing for Fresh Agricultural Products Based on the Investment of Freshness-Keeping Cost in the Distribution Process. Sustainability. 2021; 13 (14):8110.
Chicago/Turabian StyleShenjun Zhu; Hongming Fu; Yanhui Li. 2021. "Optimization Research on Vehicle Routing for Fresh Agricultural Products Based on the Investment of Freshness-Keeping Cost in the Distribution Process." Sustainability 13, no. 14: 8110.
This paper proposes a quantum game to study the food loss and waste (FLW) reduction in a two-echelon food supply chain (FSC) consisting of single supplier and single retailer. First, a Non-zero-sum game model based on the efforts of supplier and retailer in the process of FLW reduction is developed. Then, the classic strategy space is extended to quantum strategy space. The results show that in both classical environment and the separable quantum game scenario, it is difficult to achieve the Pareto optimal strategy of the two parties adopting the full effort strategy, because the full-effort party will bear the risk of betrayal by the non-effort party. However, in the context of maximally entangled quantum game, the risk causing by the non-effort party are borne by himself rather than the full-effort party. Correspondingly, both parties will adopt the full effort strategy to achieve a win-win situation and improve FLW in FSC significantly. Furthermore, an entanglement contract is proposed to ensure that neither of them has the motivation to deviate from the quantum strategy. Based on these findings, some managerial implications are presented to improve the level of cooperation and effort of the supplier and the retailer on FLW reduction.
Yanhui Li; Yan Zhao; Jing Fu; Lu Xu. Reducing food loss and waste in a two-echelon food supply chain: A quantum game approach. Journal of Cleaner Production 2020, 285, 125261 .
AMA StyleYanhui Li, Yan Zhao, Jing Fu, Lu Xu. Reducing food loss and waste in a two-echelon food supply chain: A quantum game approach. Journal of Cleaner Production. 2020; 285 ():125261.
Chicago/Turabian StyleYanhui Li; Yan Zhao; Jing Fu; Lu Xu. 2020. "Reducing food loss and waste in a two-echelon food supply chain: A quantum game approach." Journal of Cleaner Production 285, no. : 125261.
In situations where an organization has limited human resources and a lack of multi-skilled employees, organizations pay more and more attention to cost control and personnel arrangements. Based on the consideration of the service personnel scheduling as well as the routing arrangement, service personnel of different skills were divided into different types according to their multiple skills. A mathematical programming model was developed to reduce the actual cost of organization. Then, a hybrid meta heuristic that combines a tabu search algorithm with a simulated annealing was designed to solve the problem. This meta heuristic employs several neighborhood search operators and integrates the advantages of both the tabu search algorithm and the simulated annealing algorithm. Finally, the stability and validity of the algorithm were validated by the tests of several kinds of examples.
Zhiping Zuo; Yanhui Li; Jing Fu; Jianlin Wu. Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints. Mathematics 2019, 7, 598 .
AMA StyleZhiping Zuo, Yanhui Li, Jing Fu, Jianlin Wu. Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints. Mathematics. 2019; 7 (7):598.
Chicago/Turabian StyleZhiping Zuo; Yanhui Li; Jing Fu; Jianlin Wu. 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints." Mathematics 7, no. 7: 598.
Network interconnection and information sharing among firms and their departments expose them to cybersecurity breaches. Traditional cybersecurity studies have paid little attention to the reallocation of security investment within firms. This paper proposes a mathematical model for optimal allocation of cybersecurity investment among headquarters and branches with budget constraints. The differences in size of information sets and system interconnection have been taken into account. The responses of optimal allocation to internal and external factors, such as the portion of branch information set, the propagation probability, the budget constraints, and the intrinsic vulnerability, have been studied in deep both theoretically and numerically. Analysis results indicate that the group will give priority to protecting headquarters when the total budget is small and intrinsic vulnerability is high. The security investment allocated to each branch increases with budget, propagation probability and portion of information set, but never exceeds 1 / ( n + 1 ) of total budget. Numerical simulations also verify that security information sharing among headquarters and branches can help improve the efficiency of security investment in the whole system. Furthermore, the findings of this paper will draw attention to the reallocation of cybersecurity investment within a business group and help cybersecurity managers to develop investment allocation strategies and policies.
Lu Xu; Yanhui Li; Jing Fu. Cybersecurity Investment Allocation for a Multi-Branch Firm: Modeling and Optimization. Mathematics 2019, 7, 587 .
AMA StyleLu Xu, Yanhui Li, Jing Fu. Cybersecurity Investment Allocation for a Multi-Branch Firm: Modeling and Optimization. Mathematics. 2019; 7 (7):587.
Chicago/Turabian StyleLu Xu; Yanhui Li; Jing Fu. 2019. "Cybersecurity Investment Allocation for a Multi-Branch Firm: Modeling and Optimization." Mathematics 7, no. 7: 587.
The online-to-offline (O2O) community supermarket is currently a popular O2O business model in China. Owing to the small lot-size, high frequency, time-sensitive, and dynamic arrival of online customer orders, many O2O community supermarkets face challenges in how to pick up the dynamic arrival orders and deliver them to customers with minimum makespan and delivery cost. To achieve the global optimal order fulfillment performance, we study the online integrated order picking and delivery problem for an O2O community supermarket, and order pickers’ learning effects are considered to better plan the integrated problem. To propose a feasible and efficient schedule, the online algorithm A is established, and the competitive ratio is proved to be 2 theoretically. To further verify the effectiveness and efficiency of algorithm A in practice, we summarize the actual order fulfillment rules (named A1), and conduct numerical experiments to compare algorithm A with A1. Moreover order pickers’ workforce characteristics are varied to evaluate the learning effects on the order fulfillment process. The results show that Algorithm A performs better than A1 in different situations, and considering pickers’ learning effects is significant for the accuracy and predictability of order fulfillment process.
Jun Zhang; Feng Liu; Jiafu Tang; Yanhui Li. The online integrated order picking and delivery considering Pickers’ learning effects for an O2O community supermarket. Transportation Research Part E: Logistics and Transportation Review 2019, 123, 180 -199.
AMA StyleJun Zhang, Feng Liu, Jiafu Tang, Yanhui Li. The online integrated order picking and delivery considering Pickers’ learning effects for an O2O community supermarket. Transportation Research Part E: Logistics and Transportation Review. 2019; 123 ():180-199.
Chicago/Turabian StyleJun Zhang; Feng Liu; Jiafu Tang; Yanhui Li. 2019. "The online integrated order picking and delivery considering Pickers’ learning effects for an O2O community supermarket." Transportation Research Part E: Logistics and Transportation Review 123, no. : 180-199.