Online first | |
Open Access Article | |
1. |
A study on the competition and cooperation relationship of China's photovoltaic supply chain under the policy guidance
, Available Online, April, 4, 2024 Fei Zhuang, Jun Hu and Jie Wu PDF (685K) |
Abstract: 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. DOI: 10.5267/j.ijiec.2024.4.003 Keywords: Competition policy, Industrial policy, Collaborative strategy | |
Open Access Article | |
2. |
The impacts of blockchain adoption in fourth party logistics service quality management
, Available Online, April, 4, 2024 Lanhao Wang, Hongyan Wang, Min Huang and Wei Dai PDF (685K) |
Abstract: 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. DOI: 10.5267/j.ijiec.2024.4.002 Keywords: Fourth party logistics, Blockchain, Logistics service quality improvement, Revenue sharing contract | |
Open Access Article | |
3. |
Change point analysis of events in social networks: An online convex optimization approach
, Available Online, April, 4, 2024 Arya Karami and Seyed Taghi Akhavan Niaki PDF (685K) |
Abstract: Nowadays, online social networks play a crucial role in shaping human communication in various life activities. Social Network Analysis (SNA) provides valuable insights for businesses, authorities, and platform owners. One of the challenging tasks in SNA is detecting sequential change points in observed events in social networks when the parameters of statistical distribution of post-change networks are unknown. This challenging problem is particularly prominent in various real-world network systems, especially when the events in the networks can be modeled through a Hawkes process. Identifying change points in the stream of social network data, where the underlying statistical properties undergo significant changes, necessitates the development of adaptive online algorithms. Additionally, in cases where the use of maximum likelihood estimators is impractical or when no exact recursive function for likelihood is available, addressing this issue becomes more complex. This paper proposes likelihood estimators using online convex optimization methods, incorporating the adaptive moment estimation (ADAM) algorithm. The proposed method is seamlessly integrated into the sequential anomaly detection procedure for events in social networks. Experimental results on monitoring time between events demonstrate lower Expected Delay Detection (EDD), indicating the superiority of the proposed algorithm in both synthetic and real-world datasets such as Facebook and contact networks of individuals causing disease transmission. The proposed robust solution provides an efficient practical tool in situations where traditional methods face limitations in swift detection with high accuracy. DOI: 10.5267/j.ijiec.2024.4.001 Keywords: Social network events monitoring, Sequential Change Point detection, Convex Optimization, ADAM algorithm | |
Open Access Article | |
4. |
A multi objective optimization framework for robust and resilient supply chain network design using NSGAII and MOPSO algorithms
, Available Online, March, 26, 2024 Ahmad Reza Rezaei and Qiong Liu PDF (685K) |
Abstract: 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. DOI: 10.5267/j.ijiec.2024.3.003 Keywords: Resilient supply chain, Robust optimization, Taguchi, NSGAII, MOPSO | |
Open Access Article | |
5. |
Introduce free replacement extended warranty and bundle it? Optimal new extended warranty introduction strategy
, Available Online, March, 26, 2024 Kaiying Cao and Yunyi Su PDF (685K) |
Abstract: 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. DOI: 10.5267/j.ijiec.2024.3.002 Keywords: Extended warranty, Free replacement, Bundling problem, Pricing | |
Open Access Article | |
6. |
A novel hybrid algorithm of genetic algorithm, variable neighborhood search and constraint programming for distributed flexible job shop scheduling problem
, Available Online, March, 26, 2024 Leilei Meng, Weiyao Cheng, Biao Zhang, Wenqiang Zou and Peng Duan PDF (685K) |
Abstract: With a decentral and global economy, distributed scheduling problems are getting a lot of attention. This paper addresses a distributed flexible job shop scheduling problem (DFJSP) with minimizing makespan, in which three subproblems, namely operations sequencing, factory selection and machine selection must be determined. To solve the DFJSP, a novel mixed-integer linear programming (MILP) model is first developed, which can solve the small-scaled instances to optimality. Since the NP-hard characteristic of DFJSP, a hybrid algorithm (GA-VNS-CP) of genetic algorithm (GA), variable neighborhood search (VNS) and constraint programming (CP). Specifically, the GA-VNS-CP is divided into two stages. The first stage uses the hybrid meta-heuristic algorithms of GA and VNS (GA-VNS), and the VNS is designed to improve the local search ability of GA. In GA-VNS, the encoding only considers the factory selection and the operations sequencing problems, and the machine selection problem is determined by the decoding rule. Because the solution space may be limited by the decoding rule, the second stage uses the CP to extend the solution and further improve the solution. Numerical experiments based on benchmark instances are conducted to evaluate the effectiveness of the MILP model, VNS, CP and GA-VNS-CP. The experimental results show effectiveness of the MILP model, VNS and CP. Moreover, the GA-VNS-CP algorithm has better performance than traditional algorithms and improves 6 current best solutions for benchmark instances. DOI: 10.5267/j.ijiec.2024.3.001 Keywords: Distributed flexible job shop scheduling problem, Genetic algorithm, Variable neighborhood search, Constraint programming, Makespan minimization |
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