A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization

For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence.     

Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling

To enable the immediate and efficient dispatch of relief to victims of disaster, this study proposes a greedy-search-based, multi-objective, genetic algorithm capable of regulating the distribution of available resources and automatically generating a variety of feasible emergency logistics schedules for decision-makers. The proposed algorithm dynamically adjusts distribution schedules from various supply points according to the requirements at demand points in order to minimize unsatisfied demand for resources, time to delivery, and transportation costs. The proposed algorithm was applied to the case of the Chi–Chi earthquake in Taiwan to verify its performance. Simulation results demonstrate that under conditions of a limited/unlimited number of available vehicles, the proposed algorithm outperforms the MOGA and standard greedy algorithm in ‘time to delivery’ by an average of 63.57% and 46.15%, respectively, based on 10,000 iterations.     

Aligning principal and agent’s incentives: A principal–agent perspective of social networking sites

The viability of networked communities depends on the creation and disclosure of user-generated content and the frequency of user visitation (Facebook 10-K Annual Report, 2012). However, little is known about how to align the interests of user and social networking sites. In this study, we draw upon the principal-agent perspective to extend Pavlou et al.’s uncertainty mitigation model of online exchange relationships (2007) and propose an empirically tested model for aligning the incentives of the principal (user) and the agent (service provider). As suggested by Pavlou et al., we incorporated a multi-dimensional measure of trust: trust of provider and trust of members. The proposed model is empirically tested with survey data from 305 adults aged 20-55. The results support our model, delineating how real individuals with bounded rationality actually make decision about information disclosure under uncertainty in the social networking site context. There is show little to no relationship between online privacy concerns and information disclosure on online social network sites. Perceived benefits provide the linkage between the incentives of principal (user) and agent (provider) while usage intensity demonstrated the most significant impact on information disclosure. We argue that the phenomenon may be explained through Communication Privacy Management Theory. The present study enhances our understanding of agency theory and human judgment theory in the context of social media. Practical implications for understanding and facilitating online social exchange relationships are also discussed.     

Interactive fuzzy stochastic multi-level 0–1 programming using tabu search and probability maximization

In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.     

Incrementally building frequent closed itemset lattice

A concept lattice is an ordered structure between concepts. It is particularly effective in mining association rules. However, a concept lattice is not efficient for large databases because the lattice size increases with the number of transactions. Finding an efficient strategy for dynamically updating the lattice is an important issue for real-world applications, where new transactions are constantly inserted into databases. To build an efficient storage structure for mining association rules, this study proposes a method for building the initial frequent closed itemset lattice from the original database. The lattice is updated when new transactions are inserted. The number of database rescans over the entire database is reduced in the maintenance process. The proposed algorithm is compared with building a lattice in batch mode to demonstrate the effectiveness of the proposed algorithm.     

面向仓储系统的自动化WSAN“感知-控制”模型研究

建立正确的"感知-控制"模型是实现基于RFID和WSAN的物流仓储系统的关键。研究执行器节点自主移动环境下的多维事件协作检测和跟踪算法;研究基于合同网协议和多竞价拍卖算法的多执行器节点实时任务分配方法,并利用WSAN动态拓扑度相关性和网络同步能力的关系研究执行器的牵制控制策略;同时,基于神经网络模型和竞合博弈模型设计执行器节点的移动控制策略和编队控制策略。模型的有效性可利用扩展的UML建模方法和XMSF集成框架来评估。     

An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows

The vehicle routing problem with simultaneous pickups and deliveries and time windows (VRP-SPDTW) is the problem of optimally integrating forward (good distribution) and reverse logistics (returning materials) for cost saving and environmental protection. We constructed a general mixed integer programming model of VRP-SPDTW. The model contained some classical vehicle routing problems as special cases. We proposed an improved differential evolution algorithm (IDE) for solving this problem. In the algorithm, we firstly adopted the novel decimal coding to construct an initial population, then used some improved differential evolution operators unlike the existing algorithm, and in mutation operation, we used an integer order criterion based on natural number coding method. We introduced a penalty technical to publish the infeasible solution. In addition, in the crossover operation, we designed a self-adapting crossover probability that varied with iteration. We did some numerical experiments, and the results showed that the proposed method is effective for solving VRP-SPDTW.     

金属基仿生减阻材料元素与性能量化分析

借助灰色关联度分析方法,建立了触土部件金属基仿生减阻材料构成元素与性能之间的灰色关系分析模型,通过仿生犁壁材料的试验数据计算了仿生犁壁材料构成元素C、Re、Mn等分别与仿生性能指标接触角、硬度、成本等之间的关联度。分析了仿生犁壁材料元素构成比例与各性能指标之间的量化关系,为地面仿生机械减阻材料的研究提供了又一种科学分析方法。     

How do the internet technological developments shift the consumption pattern of paper products? Evidence from China

Using a monthly data between 2008 and 2019, this study investigated how the development of the Internet technologies has shaped the consumer consumption pattern of different types of paper products in China during this period. In detail, this study covers four major types of paper products in the Chinese market: newsprint, printing paper, household paper, and packaging paper. The developments of Internet technologies were decomposed into two aspects: the communication technology (CT) and the software platform technology (PT). Granger causality analysis was employed to determine whether the consumption pattern of paper products was affected by the development of the Internet. Furthermore, impulse-response analyses were utilized to measure how the consumption pattern of each paper product was shaped by the development of each aspect of Internet technologies, i.e., CT or PT. The empirical results suggested that the Internet developments are causing the consumption patterns shifts of all four paper products. Specifically, the consumptions of newsprint and printing paper were driven by both CT and PT. However, the consumptions of packaging paper and household paper were driven by the PT only. Compared to the development of CT, we found that the quick evolution of PT plays a more significant role in shifting people's consumption of paper products in China. The empirical results revealed by this study could provide valuable economics and policy implications to both academia and relevant industries.     

Determination of drivers for investing in cryptocurrencies through a fuzzy full consistency method-Bonferroni (FUCOM-F’B) framework

Cryptocurrencies have brought many innovations and discussions to economic life. Digital assets, which are very popular by investors, are frequently used for many purposes such as store of value, exchange, and speculation. It creates a research area that intentions cryptocurrency experts prioritize in crypto investments. In this paper, therefore, the fuzzy Full Consistency Method-Bonferroni (FUCOM-F’B) model is conducted to determine the priorities of drivers for investing in cryptocurrencies. The selected twenty-three drivers are classified based on five aspects, including functionality, financial, legal infrastructure, technology, and security. Based on the findings, “strong electronic encryption” and “use of digital signature” are the most significant drivers for preferring a cryptocurrency. A validation check is performed to verify the reliability, usefulness, and stability of the proposed approach. Further, the introduced approach allows taking the ambiguities and subjectivity into account which exist in the decision-making procedure. The suggested framework can be a helpful decision support tool for regulators, policymakers, practitioners, and cryptocurrency investors.