K
Kunkun Peng
Researcher at Wuhan University of Science and Technology
Publications - 17
Citations - 472
Kunkun Peng is an academic researcher from Wuhan University of Science and Technology. The author has contributed to research in topics: Job shop scheduling & Computer science. The author has an hindex of 7, co-authored 13 publications receiving 232 citations. Previous affiliations of Kunkun Peng include Huazhong University of Science and Technology.
Papers
More filters
Journal ArticleDOI
A Three-Stage Multiobjective Approach Based on Decomposition for an Energy-Efficient Hybrid Flow Shop Scheduling Problem
TL;DR: This paper investigates an energy-efficient hybrid flowshop scheduling problem with the consideration of machines with different energy usage ratios, sequence-dependent setups, and machine-to-machine transportation operations with a three-stage multiobjective approach based on decomposition (TMOA/D).
Journal ArticleDOI
Review on flexible job shop scheduling
TL;DR: The existing solution methods for the FJSP are classified into exact algorithms, heuristics and meta-heuristics, which are reviewed comprehensively and the real-world applications of the FjSP are introduced.
Journal ArticleDOI
An Improved Artificial Bee Colony algorithm for real-world hybrid flowshop rescheduling in Steelmaking-refining-Continuous Casting process
TL;DR: In the Improved Artificial Bee Colony (IABC), novel encoding and decoding strategies are devised to represent the solutions effectively, where a charge left-shifting strategy is designed to decrease cast break and a worst solution replacement strategy is developed to further enhance the exploitation ability.
Journal ArticleDOI
A multiobjective evolutionary algorithm based on decomposition for hybrid flowshop green scheduling problem
TL;DR: A multi-objective optimization model with the objectives of minimizing the makespan and total energy consumption is developed and a multiobjective discrete artificial bee colony algorithm (MDABC) based on decomposition is suggested to solve this complex problem.
Journal ArticleDOI
A multi-start variable neighbourhood descent algorithm for hybrid flowshop rescheduling
TL;DR: A comprehensive comparison against seven highly efficient algorithms demonstrates the superiority of the Multi-Start Variable Neighbourhood Descent (MSVND) algorithm for HFS rescheduling considering simultaneously three types of dynamic events.