Qishan Zhang

Research on location‐routing problem of reverse logistics with grey recycling demands based on PSO

Purpose – The purpose of this paper is to realize a location‐routing network optimization in reverse logistics (RL) using grey systems theory for uncertain information.Design/methodology/approach – There is much uncertain information in network optimization and location‐routing problem (LRP) of RL, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in logistics, however grey information of RL has not been covered. In the LRP of RL, grey recycling demands are taken into account. Then, a mathematics model with grey recycling demands has been constructed, and it can be transformed into grey chance‐constrained programming (GCCP) model, grey simulation and a proposed hybrid particle swarm optimization (PSO) are combined to resolve it. An example is also computed in the last part of the paper.Findings – The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about l...

A privacy preserving clustering technique using hybrid data transformation method

Despite many successful stories of data mining in a wide range of applications, this technique has raised some issues related to privacy and security of individuals. Due to these issues, data owners are often unwilling to share their sensitive information with data miners. In this paper, we present a novel method for privacy preserving clustering over centralized data. The proposed method is built upon the application of Double-Reflecting Data Perturbation Method (DRDP) and Rotation Based Translation (RBT) in order to provide secrecy of confidential numerical attributes without losing accuracy in results. The experiments demonstrate that the proposed method is effective and provides a feasible approach to balancing privacy and accuracy.

Parameters optimization of GM(1,1) model based on artificial fish swarm algorithm

Purpose – The purpose of this paper is to enhance the forecast precision of GM(1,1) model using an improved artificial fish swarm algorithm.Design/methodology/approach – An optimization model of GM(1,1) model about identifying the parameters is proposed, which takes the minimum of the average relative error as objective function and takes the development coefficient and grey action quantity as decision variables, then an improved artificial fish swarm algorithm is designed to solve the optimization model.Findings – The results show that the proposed method may enhance the precision of GM(1,1) model, and have better performance than particle swarm optimization.Practical implications – The method exposed in the paper can be used to optimize the parameters of GM(1,1) model, which is used frequently to solve the economic and management problem.Originality/value – The paper succeeds in enhancing the forecast precision of GM(1,1) model using an improved artificial fish swarm algorithm.

Parallel overlapping community discovery based on grey relational analysis

Discovering social communities or social circles from social networks is interesting and important for many applications like business advertisement, social recommendation and collaborative office. In this paper, by integrating grey relational analysis with the label propagation algorithm and the parallel framework, a new parallel algorithm for detecting overlapping communities is proposed. The similarity of the vertices is measured by the grey relational degree and the parallel computation primitives are employed to propagate the labels in parallel. The experiments on both the artificial and realworld networks demonstrate that the new algorithm is effective in detecting overlapping social communities.

4‐stage distribution network optimization of supply chain with grey demands

Purpose – The purpose of this paper is to attempt to realize a distribution network optimization in supply chain using grey systems theory for uncertain information.Design/methodology/approach – There is much uncertain information in the distribution network optimization of supply chain, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in supply chain, however grey information of the supply chain has not been covered. In the distribution problem of supply chain, grey demands are taken into account. Then, a mathematics model with grey demands has been constructed, and it can be transformed into a grey chance‐constrained programming model, grey simulation and a proposed hybrid particle swarm optimization are combined to resolve it. An example is also computed in the last part of the paper.Findings – The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about...

Identification of overlapping community structure with Grey Relational Analysis in social networks

Community structure is a very important characteristic of complex networks, detecting communities within networks has very important significance in several disciplines like computer science, physics, biology, etc. To some extent, Realworld networks exhibit overlapping community structure. To solve this problem, we devise a novel algorithm to identify overlapping communities in social networks with Grey Relational Analysis. This paper presents the edge vector which is a measure of relationships among nodes, and uses balanced closeness degree to describe edge similarity, computes edge clusters and finally obtains overlapping community structure. The effectiveness and the efficiency of the new algorithm is evaluated by experiments on both real-world and the computer-generated datasets.

Research on multi-objective location-routing problem of reverse logistics based on GRA with entropy weight

There are many objectives in location-routing problem of reverse logistics, which are helpful to improve practicability of reverse logistics. In this paper, a multi-objective programming model about location-routing of reverse logistics is proposed, and grey relational analysis and particle swarm optimization are combined to resolve it. The results of example show that the model and multi-objective algorithm are effective for dealing with multi-objective location-routing problem of reverse logistics.

Research on distribution network of supply chain with grey demands

There are various types of grey information in distribution network of supply chain, which are helpful to improve practical usefulness of distribution. In this paper, grey demands existed in supply chain have been discussed, and an optimization model of distribution network with grey demands is proposed. The model is NP-hard, and a hybrid particle swarm optimization algorithm based on grey chance-constrained programming is proposed to solve it. The results of example show that the model and the algorithm are effective for dealing with distribution problem of supply chain with grey demands.

Parameter optimization of GM(1,1) model based on artificial fish Swarm algorithm

There are many methods to improve the accuracy of GM(1,1) model and the Swarm intelligent algorithms can be used to optimize the development coefficient and grey action quantity of GM(1,1) model effectively. In this paper, an optimization GM(1,1) model about identifying the parameters is proposed, which takes the minimum of the average relative error as the objective function. Moreover, an improved artificial fish swarm algorithm is designed to solve the optimization model. The simulation results show that the proposed method may enhance the precision of GM(1,1) model, which has a better performance than Particle Swarm Optimization.

Life prediction on metal structure of port crane based on grey GM(1,1) model

The defective categories of port crane is studied in details, based on metal structure fault detection, to understand the actual status of a port crane. First the prediction of port crane life based on Paris model is introduced. But, this traditional residual life prediction is not so accurate considering fracture mechanics development. Then, the prediction model based on grey system theory is introduced for the study of port crane, and a grey model GM(1,1) of crack propagation is established. Next, a generic predict formula of life prediction of port crane is constructed. Finally, a case study is confirmed that the prediction has a good agreement with field data, and its relative error is less than 6%, so the proposed model has good precision and forecast creditability.