Xiwang Guo
Biographic Data
| ID | 9808398 |
|---|---|
| NAME | Xiwang Guo |
| GIVEN NAMES | Xiwang |
| FAMILY NAME | Guo |
| SIGNATURE | GUO X |
| AFFILIATIONS | Liaoning Shihua University |
| ORCID | 0000-0002-9142-1251 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 14 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A Hybrid Deep Learning Method With Iterative Feature Selection for Electric Load Forecasting Considering Social Activities and User Behaviors
Electric load inherently reflects the collective patterns of social activities and user behaviors, making their accurate prediction a challenging task. Accurate electric load forecasting is crucial for the planning, operation, scheduling, and market management of modern power systems, especially under the increasing complexity of residential energy consumption behaviors. From a data-driven modeling perspective, traditional load forecasting based …
Improved SAC Algorithm for Solving the Interactive Hybrid Disassembly Line Balancing Problem Considering Multiskilled Workers
With the advancement of manufacturing and the progression towards intelligent production, more and more production enterprises are focusing on the hybrid disassembly line balancing problem to enhance efficiency and reduce costs. This work presents an interactive hybrid disassembly line balancing problem considering multiskilled workers and its corresponding mathematical model. Additionally, we incorporated the concept of carbon emissions into the…
Solving Human–Robot Collaborative Circular Disassembly Line Balancing Problem via Graph Neural Network-Enhanced Proximal Policy Optimization Algorithm
Industry 5.0 promotes the transformation of manufacturing toward flexibility, personalization, and sustainability. As a critical component of closed-loop manufacturing systems, disassembly operations urgently require more flexible and efficient human–robot collaboration models. To this end, this work, for the first time, proposes a multihuman–robot collaborative circular disassembly line balancing problem. By allowing workers to move between robo…
Improved Carnivorous Plant Algorithm for Human–Robot Collaborative U-Shaped Disassembly Line Balancing With Mobile Workers
The advancement of human–robot collaboration technology has positioned remanufacturing as a crucial part of the circular economy, driving both economic growth and environmental sustainability. In the era of Industry 5.0, these technologies enhance the efficiency and flexibility of disassembly tasks. However, most research on human–robot collaborative disassembly (HRCD) line balancing overlooks the mobility of workers. This study introduces a prof…
Twin Delayed Deep Deterministic Policy Gradient Algorithm for a Heterogeneous Multifactory Remanufacturing Optimization Problem
To reduce resource consumption and environmental impact, the manufacturing industry increasingly leans towards repurposing, repairing, or updating products. In a multifactory environment, considering the disassembly line balancing problem helps enterprises improve production efficiency and reduce costs. Thus, this work proposes a heterogeneous multifactory remanufacturing optimization problem, considering the disassembly techniques and U-shaped d…
Multifactory Disassembly Process Optimization Considering Worker Posture
The escalating consumption and disposal of electronic products have spurred a pressing demand for environmental conservation. Traditional disassembly factories encounter challenges when handling discarded products from various locations, including high costs and limited flexibility. This study addresses a multifactory disassembly process optimization problem, taking into account worker posture and the selection of disassembly line types. Subseque…
Modeling and Optimization of Multiproduct Human–Robot Collaborative Hybrid Disassembly Line Balancing With Resource Sharing
Efficient disassembly is essential for the reintegration of end-of-life products into the remanufacturing process. Previous studies utilize human–robot collaboration and parallel workstations to enhance disassembly efficiency. However, the disassembly lines in these studies are typically independent of each other. As the number of disassembly lines in a plant increases, labor resources such as workers and robots become redundant, leading to low r…
Multifactory Remanufacturing Process Optimization Considering Worker Scheduling
Multifactory remanufacturing is a widely adopted sustainable manufacturing approach nowadays. Its complexity lies in coordinating the dismantling, remanufacturing, and resource circulation among factories to maximize resource reuse and minimize environmental impact. Proper worker scheduling is crucial in this process to ensure efficient workflow and maximal resource utilization. This study proposes and addresses an optimization problem for multif…
A Salp Swarm Algorithm for Parallel Disassembly Line Balancing Considering Workers With Government Benefits
Proper disassembly operations organization and workstation assignment can help increase the efficiency of disassembly systems that are critical for recycling and remanufacturing of end-of-life (EOL) products. A parallel disassembly system layout allows diversification of disassembly tasks and increases flexibility. In this work, a parallel disassembly balancing model considering hiring workers with government benefits (WGB) is established. To qui…
An Improved Fruit Fly Optimization Algorithm for Disassembly Lines Requiring Multiskilled Workers
Waste recycling is an important part of resource reuse and environmental protection. The study of disassembly lines deals with the process of recycling and remanufacturing end-of-life products. The performance of a disassembly line is affected by many factors, especially the operation cost of workstations, the precedence relationships among disassembly tasks, the skill level of workers, and their learning speed. This study considers the learning …
Monetary Policy, Investor Sentiment, and the Asymmetric Jump Risk of Chinese Stock Market
To investigate the impacts of monetary policies on the jump risk of Chinese stock market, we introduce them into an exponential generalized autoregressive conditional heteroskedasticity with autoregressive jump intensity (EGARCH-ARJI) model. A new jump model, i.e., the EGARCH-ARJI model with monetary policy (EGARCH-AM), is constructed. Moreover, investor sentiment is considered to investigate the interaction effect of a monetary policy and invest…
Dynamic Dependence and Hedging of Stock Markets: Evidence From Time-Varying Copula With Asymmetric Markovian Models
To study the asymmetric jump behaviors of the stock markets, we propose a novel autoregressive conditional jump intensity (ARJI)—generalized autoregressive conditional heteroskedasticity (GARCH) model with a Markov chain. Compared with the existing models, it considers the asymmetric effects of the positive and negative shocks on jump volatilities. It is proposed to estimate the asymmetric jump volatilities of the stock markets in mainland China …
Multiobjective U-Shaped Disassembly Line Balancing Problem Considering Human Fatigue Index and an Efficient Solution
The progress of science and technology speeds up the replacement of products and produces a large number of end-of-life products. Traditional incineration causes a waste of resources and pollution to the environment. Disassembling and recycling end-of-life products are the recommended way to maximize the utilization of resources and reduce environmental pollution. Disassembly performance is affected by many factors, such as the disassembly postur…
Loss Aversion Robust Optimization Model Under Distribution and Mean Return Ambiguity
From the aspect of behavioral finance, which is an emerging area integrating human behavior into finance, this work studies a robust portfolio problem for loss-averse investors under distribution and mean return ambiguity. A loss-aversion distributionally-robust optimization model is constructed if the return distribution of risky assets is unknown. Then, under the premise that the mean returns of risky assets belong to an ellipsoidal uncertainty…
No prominent works on this page.
Multiobjective U-Shaped Disassembly Line Balancing Problem Considering Human Fatigue Index and an Efficient Solution
The progress of science and technology speeds up the replacement of products and produces a large number of end-of-life products. Traditional incineration causes a waste of resources and pollution to the environment. Disassembling and recycling end-of-life products are the recommended way to maximize the utilization of resources and reduce environmental pollution. Disassembly performance is affected by many factors, such as the disassembly postur…
Loss Aversion Robust Optimization Model Under Distribution and Mean Return Ambiguity
From the aspect of behavioral finance, which is an emerging area integrating human behavior into finance, this work studies a robust portfolio problem for loss-averse investors under distribution and mean return ambiguity. A loss-aversion distributionally-robust optimization model is constructed if the return distribution of risky assets is unknown. Then, under the premise that the mean returns of risky assets belong to an ellipsoidal uncertainty…
A Salp Swarm Algorithm for Parallel Disassembly Line Balancing Considering Workers With Government Benefits
Proper disassembly operations organization and workstation assignment can help increase the efficiency of disassembly systems that are critical for recycling and remanufacturing of end-of-life (EOL) products. A parallel disassembly system layout allows diversification of disassembly tasks and increases flexibility. In this work, a parallel disassembly balancing model considering hiring workers with government benefits (WGB) is established. To qui…
An Improved Fruit Fly Optimization Algorithm for Disassembly Lines Requiring Multiskilled Workers
Waste recycling is an important part of resource reuse and environmental protection. The study of disassembly lines deals with the process of recycling and remanufacturing end-of-life products. The performance of a disassembly line is affected by many factors, especially the operation cost of workstations, the precedence relationships among disassembly tasks, the skill level of workers, and their learning speed. This study considers the learning …
Monetary Policy, Investor Sentiment, and the Asymmetric Jump Risk of Chinese Stock Market
To investigate the impacts of monetary policies on the jump risk of Chinese stock market, we introduce them into an exponential generalized autoregressive conditional heteroskedasticity with autoregressive jump intensity (EGARCH-ARJI) model. A new jump model, i.e., the EGARCH-ARJI model with monetary policy (EGARCH-AM), is constructed. Moreover, investor sentiment is considered to investigate the interaction effect of a monetary policy and invest…
Dynamic Dependence and Hedging of Stock Markets: Evidence From Time-Varying Copula With Asymmetric Markovian Models
To study the asymmetric jump behaviors of the stock markets, we propose a novel autoregressive conditional jump intensity (ARJI)—generalized autoregressive conditional heteroskedasticity (GARCH) model with a Markov chain. Compared with the existing models, it considers the asymmetric effects of the positive and negative shocks on jump volatilities. It is proposed to estimate the asymmetric jump volatilities of the stock markets in mainland China …
Improved Carnivorous Plant Algorithm for Human–Robot Collaborative U-Shaped Disassembly Line Balancing With Mobile Workers
The advancement of human–robot collaboration technology has positioned remanufacturing as a crucial part of the circular economy, driving both economic growth and environmental sustainability. In the era of Industry 5.0, these technologies enhance the efficiency and flexibility of disassembly tasks. However, most research on human–robot collaborative disassembly (HRCD) line balancing overlooks the mobility of workers. This study introduces a prof…
Twin Delayed Deep Deterministic Policy Gradient Algorithm for a Heterogeneous Multifactory Remanufacturing Optimization Problem
To reduce resource consumption and environmental impact, the manufacturing industry increasingly leans towards repurposing, repairing, or updating products. In a multifactory environment, considering the disassembly line balancing problem helps enterprises improve production efficiency and reduce costs. Thus, this work proposes a heterogeneous multifactory remanufacturing optimization problem, considering the disassembly techniques and U-shaped d…
Multifactory Disassembly Process Optimization Considering Worker Posture
The escalating consumption and disposal of electronic products have spurred a pressing demand for environmental conservation. Traditional disassembly factories encounter challenges when handling discarded products from various locations, including high costs and limited flexibility. This study addresses a multifactory disassembly process optimization problem, taking into account worker posture and the selection of disassembly line types. Subseque…
Modeling and Optimization of Multiproduct Human–Robot Collaborative Hybrid Disassembly Line Balancing With Resource Sharing
Efficient disassembly is essential for the reintegration of end-of-life products into the remanufacturing process. Previous studies utilize human–robot collaboration and parallel workstations to enhance disassembly efficiency. However, the disassembly lines in these studies are typically independent of each other. As the number of disassembly lines in a plant increases, labor resources such as workers and robots become redundant, leading to low r…
Multifactory Remanufacturing Process Optimization Considering Worker Scheduling
Multifactory remanufacturing is a widely adopted sustainable manufacturing approach nowadays. Its complexity lies in coordinating the dismantling, remanufacturing, and resource circulation among factories to maximize resource reuse and minimize environmental impact. Proper worker scheduling is crucial in this process to ensure efficient workflow and maximal resource utilization. This study proposes and addresses an optimization problem for multif…
A Hybrid Deep Learning Method With Iterative Feature Selection for Electric Load Forecasting Considering Social Activities and User Behaviors
Electric load inherently reflects the collective patterns of social activities and user behaviors, making their accurate prediction a challenging task. Accurate electric load forecasting is crucial for the planning, operation, scheduling, and market management of modern power systems, especially under the increasing complexity of residential energy consumption behaviors. From a data-driven modeling perspective, traditional load forecasting based …
Improved SAC Algorithm for Solving the Interactive Hybrid Disassembly Line Balancing Problem Considering Multiskilled Workers
With the advancement of manufacturing and the progression towards intelligent production, more and more production enterprises are focusing on the hybrid disassembly line balancing problem to enhance efficiency and reduce costs. This work presents an interactive hybrid disassembly line balancing problem considering multiskilled workers and its corresponding mathematical model. Additionally, we incorporated the concept of carbon emissions into the…
Solving Human–Robot Collaborative Circular Disassembly Line Balancing Problem via Graph Neural Network-Enhanced Proximal Policy Optimization Algorithm
Industry 5.0 promotes the transformation of manufacturing toward flexibility, personalization, and sustainability. As a critical component of closed-loop manufacturing systems, disassembly operations urgently require more flexible and efficient human–robot collaboration models. To this end, this work, for the first time, proposes a multihuman–robot collaborative circular disassembly line balancing problem. By allowing workers to move between robo…
Computer Science (9 works) · Engineering (8 works) · Manufacturing Process and Optimization (8 works) · Assembly Line Balancing Optimization (5 works) · Mathematics (5 works) · Advanced Manufacturing and Logistics Optimization (4 works) · Mathematical optimization (4 works) · Optimization algorithm (4 works) · Reliability engineering (4 works) · Algorithm (3 works)