Z
Ziyan Zhao
Researcher at Northeastern University (China)
Publications - 31
Citations - 521
Ziyan Zhao is an academic researcher from Northeastern University (China). The author has contributed to research in topics: Computer science & Job shop scheduling. The author has an hindex of 5, co-authored 15 publications receiving 83 citations. Previous affiliations of Ziyan Zhao include Liaoning University of Petroleum and Chemical Technology & New Jersey Institute of Technology.
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Dual-Objective Mixed Integer Linear Program and Memetic Algorithm for an Industrial Group Scheduling Problem
TL;DR: In this article, a new bi-objective serial-batch group scheduling problem considering the constraints of sequence-dependent setup time, release time, and due time is proposed. But the problem is not solved by a memetic algorithm.
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Decomposition Method for New Single-Machine Scheduling Problems From Steel Production Systems
TL;DR: A two-stage decomposition method is proposed such that an industrial size problem can be solved and can get an optimal solution of the concerned problem with one-week-scale batches and jobs in short time, thereby proving the readiness to put it in industrial use.
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Iterated Greedy Algorithms for Flow-Shop Scheduling Problems: A Tutorial
TL;DR: An iterated greedy algorithm (IGA) is a simple and powerful heuristic algorithm that is widely used to solve flow-shop scheduling problems (FSPs), an important branch of production scheduling problems as discussed by the authors.
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Heuristic Scheduling of Batch Production Processes Based on Petri Nets and Iterated Greedy Algorithms
TL;DR: Four iterated greedy algorithm-based methods by using different neighborhood structures and integrating a variable neighborhood descent method are developed to solve the scheduling problem of a batch production process, i.e., wire rod and bar rolling, which is modeled by a Petri net (PN).
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Stochastic Hybrid Discrete Grey Wolf Optimizer for Multi-Objective Disassembly Sequencing and Line Balancing Planning in Disassembling Multiple Products
TL;DR: In this article , a stochastic multi-product multi-objective disassembly-sequencing-line balancing problem aiming at maximizing disassembly profit and minimizing energy consumption and carbon emission is proposed.