Key Laboratory of Computer Technologies Application of Yunnan Province

Kunming, China

Key Laboratory of Computer Technologies Application of Yunnan Province

Kunming, China
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Chen S.-F.,Kunming University of Science and Technology | Chen S.-F.,Key Laboratory of Computer Technologies Application of Yunnan Province | Qian B.,Kunming University of Science and Technology | Qian B.,Key Laboratory of Computer Technologies Application of Yunnan Province | And 4 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

In this paper, an enhanced estimation of distribution algorithm (EEDA) is proposed for the no-wait job shop scheduling problem (NWJSSP) with the makespan criterion, which has been proved to be strongly NP-hard. The NWJSSP can be decomposed into the sequencing and the timetabling problems. The proposed EEDA and a shift timetabling method are used to address the sequencing problem and the timetabling problem, respectively. In EEDA, the EDA-based search is applied to guiding the search to some promising sequences or regions, and an Interchange-based local search is presented to perform the search from these promising regions. Moreover, each individual or sequence of EEDA is decoded by applying a shift timetabling method to solving the corresponding timetabling problem. The experimental results show that the combination of the EEDA and the shift timetabling method can accelerate the convergence speed and is helpful in achieving more competitive results. © 2014 Springer International Publishing Switzerland.


Chen S.-F.,Kunming University of Science and Technology | Chen S.-F.,Key Laboratory of Computer Technologies Application of Yunnan Province | Qian B.,Kunming University of Science and Technology | Qian B.,Key Laboratory of Computer Technologies Application of Yunnan Province | And 4 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

In this paper, a bayesian statistical inference-based estimation of distribution algorithm (BEDA) is proposed for the re-entrant job-shop scheduling problem with sequence-dependent setup times (RJSSPST) to minimize the maximum completion time (i.e., makespan), which is a typical NP hard combinatorial problem with strong engineering background. Bayesian statistical inference (BSI) is utilized to extract sub-sequence information from high quality individuals of the current population and determine the parameters of BEDA's probabilistic model (BEDA-PM). In the proposed BEDA, BEDA-PM is used to generate new population and guide the search to find promising sequences or regions in the solution space. Simulation experiments and comparisons demonstrate the effectiveness of the proposed BEDA. © 2014 Springer International Publishing Switzerland.


Li Z.,Kunming University of Science and Technology | Li Z.,Key Laboratory of Computer Technologies Application of Yunnan Province | Qian B.,Kunming University of Science and Technology | Qian B.,Key Laboratory of Computer Technologies Application of Yunnan Province | And 3 more authors.
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | Year: 2015

Aiming at a certain kind of three-stage assembly flowshop scheduling problem which was Three-Stage Assembly Flowshop Scheduling Problem with Sequence-Dependent Setup Times (TSAFSP_SDST), an Adaptive Hybrid Estimation of Distribution Algorithm (AHEDA) was presented to minimize the weighted sum of average completion time and maximum tardiness. The generation mechanism of initial population and initial probability distribution model were proposed to make probability distribution model accumulate the high quality solutions' information properly, which could improve the search ability of AHEDA at the initial stage of evolution. To enhance AHEDA's global search ability, the adaptive update scheme based on information entropy was designed for probability distribution model, and the new population generation method was also constructed to keep excellent and good pattern. An Insert-based neighbor search was introduced to improve the local search ability. The effectiveness of the presented AHEDA was verified by computational experiments and comparisons. ©, 2015, CIMS. All right reserved.


Cao G.-L.,Kunming University of Science and Technology | Cao G.-L.,Key Laboratory of Computer Technologies Application of Yunnan Province | Hu R.,Kunming University of Science and Technology | Hu R.,Key Laboratory of Computer Technologies Application of Yunnan Province | And 4 more authors.
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | Year: 2015

For solving the Capacitated Vehicle Routing Problem (CVRP), an Effective Hybrid Quantum Evolutionary Algorithm (EHQEA) was presented. The solution generation method based on two-dimensional Qubit Measurement Model (QMM) and visibility was designed to realize the global search guided by QMM, which was used to find the promising regions over the solution space. An interchange operation based on the distance similar degree between customers was constructed to improve the quality of the solution. The Interchange and Inverse operations based on the problem's property were proposed to construct a two-phase hybrid variable neighborhood local search, which was utilized to execute the fast and meticulous search in the promising regions and helped the algorithm to achieve a balance between the global and local search. Simulation results and comparisons on classic benchmarks with different scales demonstrated the effectiveness and robustness of the presented EHQEA. ©, 2015, CIMS. All right reserved.


Meng X.-H.,Kunming University of Science and Technology | Meng X.-H.,Key Laboratory of Computer Technologies Application of Yunnan Province | Hu R.,Kunming University of Science and Technology | Hu R.,Key Laboratory of Computer Technologies Application of Yunnan Province | And 2 more authors.
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | Year: 2014

A hybrid population-based incremental learning algorithm, namely HPBIL, is proposed to simultaneously minimize the number of vehicles and total travel distance for the vehicle routing problem with time windows (VRPTW). In the presented HPBIL, the improved probability model of PBIL is devised to enhance global exploration ability, and a two-phase local search based on the insert and two points neighborhood exchange methods is developed to strengthen local exploitation ability. Simulation results and comparisons with other algorithms demonstrate the effectiveness and robustness of HPBIL. ©, 2014, Systems Engineering Society of China. All right reserved.


Li Z.,Kunming University of Science and Technology | Li Z.,Key Laboratory of Computer Technologies Application of Yunnan Province | Qian B.,Kunming University of Science and Technology | Qian B.,Key Laboratory of Computer Technologies Application of Yunnan Province | And 5 more authors.
Huagong Xuebao/CIESC Journal | Year: 2014

A genetic algorithm-estimation of distribution algorithm (GA-EDA) was proposed to optimize the makespan criterion for a kind of heterogeneous parallel machine scheduling problem, i. e., the heterogeneous parallel machine scheduling problem with multiple operations and sequence-dependent setup times (HPMSP_MOSST), which widely existed in chemical production. Firstly, a probability model training mechanism based on GA was presented and used to increase the information accumulation of the probability model at the initial stage of the evolution, and then the efficiency of search was improved. Secondly, an effective hybrid strategy of GA and EDA was designed to help the algorithm achieve a reasonable balance between global exploration and local exploitation abilities.computer simulation showed the effectiveness and robustness of the proposed GA-EDA. © All Rights Reserved.

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