Modeling and algorithm for resource-constrained multi-project scheduling problem based on detection and rework

Purpose To meet the requirement of establishing an effective schedule for the assembly process with overall detection and rework, this paper aims to address a new problem named resource-constrained multi-project scheduling problem based on detection and rework (RCMPSP-DR). Design/methodology/approach First, to satisfy both online and offline scheduling, a mixed integer programming model is established with a weighted bi-objective minimizing the expected makespan and the solution robustness. Second, an algorithm that combines a tabu search framework with a critical chain-based baseline generation scheme is designed. The tabu search framework focuses on searching for a reasonable resource flow representing the execution sequence of activities, while the critical chain-based baseline generation scheme establishes a buffered baseline schedule by estimating the tradeoff between two aspects of bi-objective. Findings The proposed algorithm can get solutions with gaps from −4.45% to 2.33% when compared with those obtained by the commercial MIP solver CPLEX. Moreover, the algorithm outperforms four other algorithms in terms of both objective performance and stability over instances with different weighting parameters, which reveals its effectiveness. Originality/value The represented RCMPSP-DR considering the overall detection and rework is an extension of the scheduling problem for large-scale equipment. An effective algorithm is proposed to establish the baseline schedule and determine the execution sequence of activities for the assembly process, which is significant for practical engineering applications.

SLAM: A Malware Detection Method Based on Sliding Local Attention Mechanism

Since the number of malware is increasing rapidly, it continuously poses a risk to the field of network security. Attention mechanism has made great progress in the field of natural language processing. At the same time, there are many research studies based on malicious code API, which is also like semantic information. It is a worthy study to apply attention mechanism to API semantics. In this paper, we firstly study the characters of the API execution sequence and classify them into 17 categories. Secondly, we propose a novel feature extraction method based on API execution sequence according to its semantics and structure information. Thirdly, based on the API data characteristics and attention mechanism features, we construct a detection framework SLAM based on local attention mechanism and sliding window method. Experiments show that our model achieves a better performance, which is a higher accuracy of 0.9723.

Software Crucial Functions Ranking and Detection in Dynamic Execution Sequence Patterns

Because of the sequence and number of calls of functions, software network cannot reflect the real execution of software. Thus, to detect crucial functions (DCF) based on software network is controversial. To address this issue, from the viewpoint of software dynamic execution, a novel approach to DCF is proposed in this paper. It firstly models, the dynamic execution process as an execution sequence by taking functions as nodes and tracing the stack changes occurring. Second, an algorithm for deleting repetitive patterns is designed to simplify execution sequence and construct software sequence pattern sets. Third, the crucial function detection algorithm is presented to identify the distribution law of the numbers of patterns at different levels and rank those functions so as to generate a decision-function-ranking-list (DFRL) by occurrence times. Finally, top-k discriminative functions in DFRL are chosen as crucial functions, and similarity the index of decision function sets is set up. Comparing with the results from Degree Centrality Ranking and Betweenness Centrality Ranking approaches, our approach can increase the node coverage to 80%, which is proven to be an effective and accurate one by combining advantages of the two classic algorithms in the experiments of different test cases on four open source software. The monitoring and protection on crucial functions can help increase the efficiency of software testing, strength software reliability and reduce software costs.

Stages of Formation of Railway Economic Safety Schemes

It is found that the railway economic safety system shall be formed taking into consideration current social changes in the society. There is the comprehensive approach to the formation of railway economic safety schemes. It is found that railway economic safety enforcement shall be the continuous cyclic process to be regularly improved. There is the scheme of execution sequence of railway economic safety management. It is found that while determining railway economic safety, in whole or in part, of each element, quantitative and qualitative evaluation methods shall be used and combined. There is the calculation of railway economic safety based on the determination of aggregate criterion. It is found that the selection of figures upon certain functional elements shall be made based on any threats.

Complexitor: An Educational Tool for Learning Algorithm Time Complexity in Practical Manner

Based on the informal survey, learning algorithm time complexity in a theoretical manner can be rather difficult to understand. Therefore, this research proposed Complexitor, an educational tool for learning algorithm time complexity in a practical manner. Students could learn how to determine algorithm time complexity through the actual execution of algorithm implementation. They were only required to provide algorithm implementation (i.e. source code written on a particularprogramming language) and test cases to learn time complexity. After input was given, Complexitor generated execution sequence based on test cases and determine its time complexity through Pearson correlation. An algorithm time complexity with the highest correlation value toward execution sequence was assigned as its result. Based on the evaluation, it can be concluded this mechanism is quite effective for determining time complexity as long as the distribution of given input set is balanced.