International Journal of Applied Decision Sciences (8 papers in press)
A Novel Selection Method of Network Intrusion Optimal Route Detection based on Naive Bayesian
by Yu Nuo
Abstract: In order to improve the network security performance and resist the increasingly complex and diversified network intrusion, and reduce the false alarm rate of network intrusion and improve the detection efficiency, this paper proposes the selection method of the network intrusion optimal route detection based on Naive Bayesian. We selected the feature subset of network route data by the principal component analysis and accordingly processed the network route detection sample set, getting the input characteristics of network route detection. The research selected the new low dimensional feature of network route data through linear or nonlinear transformation, and used the Naive Bayesian network structure to classify the new network route data set. Simulation results show that the proposed method can improve the detection rate of network intrusion optimal route and reduce the false alarm rate, getting a more perfect result of network intrusion detection.
Keywords: network intrusion detection; principal component analysis; PCA; normalisation; optimal route of network intrusion.
Reversion Strategy for Online Portfolio Selection with Transaction Costs
by Xingyu Yang, Huaping Li, Yong Zhang, Jin'an He
Abstract: We concern the online portfolio selection problem with transaction costs, which is an unavoidable factor in real financial trading. By exploiting the mean reversion property of stock prices, we propose a portfolio selection strategy named ``Mean Reversion strategy with Transaction Costs (MRTC)''. To avoid overmuch transaction costs, the strategy adaptively transfers a proper amount of capital between stocks to adjust the turnover. Furthermore, we conduct numerical experiments on several real market datasets, and show that our proposed algorithm outperforms the existing state-of-the-art ones when taking transaction costs into account.
Keywords: Online Portfolio Selection; Investment Strategy; Mean Reversion; Transaction Costs.
Solving group decision-making problems in manufacturing systems by an uncertain compromise ranking method
by S.M. Mousavi, N. Foroozesh, H. Gitinavard, Behnam Vahdani
Abstract: The purpose of this paper is to introduce a new modified compromise ranking method (VIKOR) known as sorting the possible alternatives and determining the compromise solution under interval-valued hesitant fuzzy sets (IVHFSs) for solving group decision-making problems in manufacturing systems. Proposed interval-valued hesitant fuzzy modified VIKOR (IVHF-MVIKOR) method utilizes the membership degrees to demonstrate the degrees of satisfiability for each possible alternative according to selected criteria for the manufacturing assessments. Then, a new index for relative importance weight of the DMs is introduced with the extended fuzzy sets. Also, some operations in the proposed IVHF-MVIKOR method are developed for manufacturing decision problems. Then, new indexes are presented with interval-valued hesitant fuzzy hamming distance measure for the purpose of rankings. Finally, by presenting a practical example in flexible manufacturing systems, the performance of IVHF-MVIKOR method is evaluated and compared with two well-known methods under interval-valued hesitant fuzzy information.
Keywords: Interval-valued hesitant fuzzy sets (IVHFSs); group decision-making problems; manufacturing systems; modified VIKOR method; interval-valued hesitant fuzzy hamming distance measure.
Vehicle Scheduling Model of Emergency Logistics Distribution Based on Internet of Things
by Qing CHANG
Abstract: Considering that emergency logistics distribution has the timeliness, weak economy, and the traffic road condition and so on, based on reasonable assumptions, we effectively scheduled vehicles to maximize the demand for emergency logistics within the requested time. This paper proposes an emergency logistics vehicle scheduling model based on Internet of things. Firstly, we built the model of emergency logistics distribution vehicle scheduling problem. Our research built a model of emergency logistics distribution vehicle scheduling by using the model of division time, and gave the interrelation of constraint condition. On this basis, this paper combined genetic algorithm and ant colony algorithm for the vehicle scheduling model design and parameter selection, which improved the efficiency of emergency logistics distribution. Simulation results show that the proposed model can effectively increase the transport efficiency and reduce transportation costs, and has strong practical value. It is suited for post-disaster emergency logistics distribution vehicle scheduling.
Keywords: Internet of things; Emergency logistics; Vehicle scheduling model; Simulation.
Performance Assessment Model for Bank Clients Services and Business Development Process: A Constructivist Proposal
by Leonardo Ensslin, Sandra Ensslin, Ademar Dutra, Andre Longaray, Vinicius Dezem
Abstract: The banking sector has been characterised by ongoing evolution in service rendering, driven by advances in technology, changes in client profiles, and susceptibility to political and economic issues. This article describes the development stages of a decision-aid system to manage the customer relations and business development process with bank clients, using the perceptions of both managers and clients. The investigation was conducted through a case study, using the constructivist MCDA. The elaborated model allowed for the structured identification and evaluation of 99 descriptors. Through use of the model, managers gained focus and confidence, customers reacted with gratitude and loyalty, and stakeholders realised the importance of the approach as they had a clear understanding of the goals.
Keywords: bank assessment model; multi-criteria methods; decision aid; bank client services; constructivist MCDA.
A Fast Dynamic Programming Algorithm to a Varied Capacity Problem in Vehicle Routing
by PengLe Zhang, Yajie Dou
Abstract: As a typical combinational optimization problem, the researches on Vehicle Routing Problem (VRP) mostly focus on the case when vehicle loading capability is certain. In fact, the vehicle loading capability often changes with multi-type vehicles, varying goods size and customer's requirement alter. Thus, a varied capacity vehicle routing problem (VCVRP) is introduced and a fast dynamic programming algorithm is presented based on the K-step Best Fit Deceasing and Minimum Spanning Tree methods, the algorithms can serve as an approximate decoupling between the goods packing problem and router selection problem in VCVRP. Besides, the theoretical analysis on the upper bound of vehicle trip and local minimization based on short-path priority principle are carried out theoretically. Finally, an example about varied capacity vehicle logistics transportation task is given with quality and performance analysis on different parameters and scales, to illustrate the feasibilities and advantages of the proposed algorithm.
Keywords: logistic systems; dynamic programming; varied capacity vehicle routing problem; VCVRP; fast algorithm; heuristic algorithm.
Audit Evidence and Modelling Audit Risk Using Goal Programming
by Saeed Askary, Jean-Paul M. Arnaout, Naser Abu Ghazaleh
Abstract: Managing audit risk and allocating auditing resources are among the major problems faced by external auditors. To address this problem, this paper introduces external auditors to Goal Programming (GP), an innovative technique that can be used in Audit Risk Models (ARM). The value of an audit report depends on the audit risk: the lower the audit risk, the higher the quality of the audit report. Using GP when calculating audit risk enhances audit quality by helping auditors to manage the multi-choice decision making. However, to date there has been no consideration of GP in ARM. This research provides insights that can be used by audit firms of any size, including those in the Big 4.
Keywords: audit risk model; ARM; audit evidence; control risk; detection risk; goal programming; GP.
Fuzzy Evaluation Mechanism of Trust Chain under Embedded Trusted Computing
by Gang Li
Abstract: This paper proposes a trust chain evaluation mechanism based on fuzzy theory under embedded trusted computing. Firstly, this method described the trusted computing, the trusted computing platform, embedded system, which showed the important position of the trust chain in dependable computing. Then, in the process of the entity evaluation of trust chain, according to the influencing factors of trust chain in the trusted computing, considering the indirect trust degree, completed the establishment of evaluation method of trusted computing model based on the fuzzy set theory. Finally, combined the fuzzy logic inference with the trust transitivity, we proposed a trust chain evaluation mechanism based on similarity, and introduced the time decay function and adaptive weight coefficient to give the trust updating model. Simulation experiment shows that the proposed method can effectively improve the reliability of trust chain evaluation in embedded trusted computing, which has good application value.
Keywords: Embedded; Trusted computing; Fuzzy theory; Trust chain evaluation.