Disruption management for vehicle routing problem with time-window changes

Ju, Chunhua; Zhou, Guanglan; Chen, Tinggui

doi:10.1504/ijstl.2017.080568

Cited by 8 publications

(4 citation statements)

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“…In 2007, Basturk et al (2007) further applied ABC to numerical optimization with constraints, and obtained good results. In respect of combination optimization, Singh (2009) successfully uncovered leafconstrained minimum spanning tree from an undirected, weighted graph with ABC algorithm; Ju et al (2017) presented a solution for disruption problem in logistic distribution with improved ABC algorithm, with better performance than general heuristic solutions; and Garg (2014) solved structural engineering design optimization problems with penalty guided ABC algorithm, and experimental results showed that solutions obtained by the proposed approach were superior to those best solutions by typical approaches in the literature. And against problems of unconstrained numerical optimization, researchers have proved that comprehensive performance of ABC algorithm is better than those of other intelligent algorithms (Chen and Xiao, 2014).…”

Section: Realization Process Of Classic Association Rule Mining Algorithmmentioning

confidence: 99%

Library personalized recommendation service method based on improved association rules

Kai-gang

Chen

Cong

2017

LHT

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Purpose Nowadays, database management system has been applied in library management, and a great number of data about readers’ visiting history to resources have been accumulated by libraries. A lot of important information is concealed behind such data. The purpose of this paper is to use a typical data mining (DM) technology named an association rule mining model to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library. Design/methodology/approach Association rule mining algorithm is applied to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library. Findings Through an analysis on record of book borrowing by readers, library manager can recommend books that may be interested by a reader based on historical borrowing records or current book-borrowing records of the reader. Research limitations/implications If many different categories of book-borrowing problems are involved, it will result in large length of encoding as well as giant searching space. Therefore, future research work may be considered in the following aspects: introduce clustering method; and apply association rule mining method to procurement of book resources and layout of books. Practical implications The paper provides a helpful inspiration for Big Data mining and software development, which will improve their efficiency and insight on users’ behavior and psychology. Social implications The paper proposes a framework to help users understand others’ behavior, which will aid them better take part in group and community with more contribution and delightedness. Originality/value DM technology has been used to discover information concealed behind Big Data in library; the library personalized recommendation problem has been analyzed and formulated deeply; and a method of improved association rules combined with artificial bee colony algorithm has been presented.

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Section: Realization Process Of Classic Association Rule Mining Algorithmmentioning

confidence: 99%

Library personalized recommendation service method based on improved association rules

Kai-gang

Chen

Cong

2017

LHT

Self Cite

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“…In addition, because of the large number of variables involved in the model and the high complexity of the solution, it is difficult to solve this kind of NP-hard problem by general exact algorithms. Since artificial bee colony algorithm simulates bee colony's behavior of foraging in nature and boasts high solving efficiency, simple algorithm, fewer parameters, and strong robustness [20,21], this paper designs an improved artificial bee colony algorithm to solve the problem.…”

Section: Algorithm Design For Problem Solvingmentioning

confidence: 99%

Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Chen

Yang

et al. 2020

Complexity

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It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

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“…These activities or tasks and their operation logic relationships can be presented by a directed graph formed by directed connection arcs, as shown in Figure 1. In the supply chain partner selection problem, the supplier network is composed of many upstream and downstream enterprises; thus it can be abstracted into a weighteddirected graph [22]. And presents the set of nodes; presents the set of edges; the number of nodes is ; the number of edges is ; the set = ⋃ =1 presents the available node supplier enterprises on supplier network and presents the set of edges [23].…”

Section: Problems Analysismentioning

confidence: 99%

Modeling Multilevel Supplier Selection Problem Based on Weighted-Directed Network and Its Solution

Wei

Zuo

Jiang

et al. 2017

Discrete Dynamics in Nature and Society

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With the rapid development of economy, the supplier network is becoming more and more complicated. It is important to choose the right suppliers for improving the efficiency of the supply chain, so how to choose the right ones is one of the important research directions of supply chain management. This paper studies the partner selection problem from the perspective of supplier network global optimization. Firstly, this paper discusses and forms the evaluation system to estimate the supplier from the two indicators of risk and greenness and then applies the value as the weight of the network between two nodes to build a weighted-directed supplier network; secondly, the study establishes the optimal combination model of supplier selection based on the global network perspective and solves the model by the dynamic programming-tabu search algorithm and the improved ant colony algorithm, respectively; finally, different scale simulation examples are given to testify the efficiency of the two algorithms. The results show that the ant colony algorithm is superior to the tabu search one as a whole, but the latter is slightly better than the former when network scale is small.

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Disruption management for vehicle routing problem with time-window changes

Cited by 8 publications

References 0 publications

Library personalized recommendation service method based on improved association rules

Library personalized recommendation service method based on improved association rules

Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Modeling Multilevel Supplier Selection Problem Based on Weighted-Directed Network and Its Solution

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