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Xueping Li
Researcher at University of Tennessee
Publications - 152
Citations - 2413
Xueping Li is an academic researcher from University of Tennessee. The author has contributed to research in topics: Computer science & Supply chain. The author has an hindex of 22, co-authored 133 publications receiving 1902 citations. Previous affiliations of Xueping Li include University Of Tennessee System & University of Tennessee Health Science Center.
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Developing a value stream map to evaluate breakdown maintenance operations
TL;DR: In this article, the authors developed a Value Stream Mapping (VSM) tool to evaluate Breakdown Maintenance Activities (BMA) activities within a manufacturing plant, which refers to systematically evaluating the non-value added (NVA) activities.
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Single batch processing machine scheduling with two-dimensional bin packing constraints
Xueping Li,Kaike Zhang +1 more
TL;DR: A mixed integer programming (MIP) model is presented and heuristic algorithms to tackle the problem of minimizing the makespan for jobs on a single batch processing machine (BPM) are developed, including four single-sequence based heuristics, a biased random-key genetic algorithm (BRKGA), and a hybrid bin loading (HBL) algorithm.
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Web server QoS models: applying scheduling rules from production planning
TL;DR: This paper presents web server QoS models that use a single queue, along with scheduling rules from production planning in the manufacturing domain, to differentiate QoS for classes of web service requests with different priorities.
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A bi-objective scheduling problem on batch machines via a Pareto-based ant colony system
Rui Xu,Huaping Chen,Xueping Li +2 more
TL;DR: A scheduling algorithm based on the framework of a multi-objective ant colony optimization (MOACO) approach called a Pareto-based ant colony system (PACS) was developed and demonstrated that PACS had a superior performance compared to other benchmark algorithms, especially for large job instances.
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Cooperative maximal covering models for humanitarian relief chain management
TL;DR: This study examines the general structure in humanitarian relief chain logistics, and focuses on developing a maximal cooperative covering model with budget considerations to maximize the benefits to the affected population in disastrous regions.