Article
Management
Hossein Mostafaei, Pedro M. Castro, Fabricio Oliveira, Iiro Harjunkoski
Summary: This paper introduces a mixed integer linear programming model for pipeline transportation scheduling, which considers factors such as interface material generation, planned shutdowns, and local market demands, resulting in better schedules. The use of generalized disjunctive programming and convex hull reformulation of disjunctions leads to stronger and more computationally efficient formulations for large-scale industrial cases.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Chemical
Renfu Tu, Qi Liao, Liqiao Huang, Yingqi Jiao, Xuemei Wei, Yongtu Liang
Summary: Accurate estimation of remaining capacity is crucial for pipeline companies to improve their service quality and economic benefits. This study develops a mathematical model for multiproduct pipelines to obtain the optimal remaining capacity at different injection nodes during different periods. The model is validated and sensitivity analysis is conducted to identify the driving factors of the optimal remaining capacity. The comparison reveals that the tightness of delivery time has a major impact on the optimal remaining capacity, especially at downstream nodes of the pipeline. Relevant suggestions are provided to help pipeline operators make decisions based on the results.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2023)
Article
Engineering, Civil
Yulei Xu, Bin Xu, Jinzhou Song, Zhengbing Li, Yi Guo, Renfu Tu, Yongtu Liang, Hongyang Gao, Hengyu Wang
Summary: This study focuses on the operation and management of multiproduct pipelines, proposing key technologies and a scheduling model for contamination control. By reducing segment stoppage and improper interface placement, it helps to decrease the cost of contamination treatment.
JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE
(2023)
Article
Computer Science, Interdisciplinary Applications
Yamin Yan, Pedro M. Castro, Qi Liao, Yongtu Liang
Summary: This article presents a novel two-stage algorithm for the detailed scheduling of branched multiproduct pipeline systems with a single refinery and multiple depots. The algorithm can significantly reduce computational time and improve pipeline transportation capacity.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Energy & Fuels
Zhengbing Li, Yongtu Liang, Weilong Ni, Qi Liao, Ning Xu, Lichao Li, Jianqin Zheng, Haoran Zhang
Summary: Biofuel energy is recognized as a highly promising renewable energy source and promoting its extensive application can effectively reduce carbon emissions. Using existing pipelines for biofuel transportation not only meets environmental requirements, but also makes use of surplus pipeline capacity. This study developed a method to estimate the capacity of pipelines for biofuel transport, taking into account factors such as client demand, pipeline equipment limitations, and transport cycles. Results showed that pipeline length, equipment capacity, and market demand were the dominant factors affecting surplus capacity. Sharing pipeline capacity for biofuel shipment brings about economic and environmental benefits for both petroleum and pipeline companies.
Article
Engineering, Chemical
Ayush Nema, Babji Srinivasan, Thokozani Majozi, Rajagopalan Srinivasan
Summary: Many countries are currently facing a severe water crisis. Small and medium enterprises in various industrial sectors struggle to deploy complex water-reuse strategies due to lack of instrumentation and automation. This paper proposes a simple and feasible water-reuse strategy that can result in significant water savings, as demonstrated in a textile industry case study.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2021)
Article
Engineering, Civil
Yansong Li, Dong Han, Baoying Wang, Jianfei Sun
Summary: In this study, an industrial scale simulation method (ISSM) is proposed to predict the contamination and oil quality distribution in multiproduct pipelines. ISSM consists of two subalgorithms: computational domain tracking method (CDTM) and spatial domain conversion method (SDCM). CDTM reduces computational effort while SDCM adapts spatial mesh resolution according to contamination distribution. The accuracy and efficiency of ISSM are validated by numerical simulation and practical experiments. ISSM improves computational efficiency and captures the asymmetric distribution of contamination concentration along the pipeline. The framework of ISSM allows tracking oil product quality and potential development of a quality-based scheduling scheme.
JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE
(2023)
Article
Oceanography
Maxime Marin, Ming Feng, Helen E. Phillips, Nathaniel L. Bindoff
Summary: A global assessment of coastal MHWs using an ensemble approach reveals an increase in frequency and duration over the past 25 years, with main driver being long-term changes in mean SST. Differences in MHW mean intensity between products suggest sensitivity to specific SST data sets and emphasize the need for an ensemble approach in MHW analysis.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2021)
Article
Computer Science, Interdisciplinary Applications
Tim van der Weide, Qichen Deng, Bruno F. Santos
Summary: This paper applies a genetic algorithm to generate robust and efficient aircraft heavy maintenance check schedules, reducing workload and the need for frequent adjustments while considering uncertainties. A case study of a major European airline shows that the algorithm can find suitable maintenance schedules for a fleet of 45 aircraft in a short amount of time, reducing the total number of checks and increasing utilization.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Editorial Material
Computer Science, Theory & Methods
Yan Zhang, Kun Wang, Lei He
Summary: Energy Internet is a new paradigm for power generation and usage, aiming to tackle energy crisis and carbon emission by developing a revolutionary vision of a smart grid. It requires intelligent cooperation between computation and communication, along with the development of pervasive solutions for creating a complex and intelligent energy system.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Zihan Zhang, Mingbo Liu, Min Xie, Ping Dong
Summary: This paper proposes a coordinated optimization model between hydrothermal generator maintenance scheduling and long-term unit commitment, considering the network security constraints and coupling characteristics between cascade hydro plants. An improved two-stage heuristic algorithm based on the objective scaling ensemble approach is proposed to accelerate the solution of this complex problem. Simulation results show that the proposed algorithm can speed up the process of finding a near-optimal solution for large-scale systems, and the proposed model can plan out feasible and coordinated maintenance scheduling and long-term unit commitment scheme simultaneously.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Energy & Fuels
Ying-Chun Chen, Yan-Feng Li, Yan Xi, Qiang Li, Qi Lu, Jie Yang
Summary: This study investigates the aging process and mechanism of polyethylene buried pipelines through mechanical and chemical property tests and microstructural analysis. The results reveal that cross-linking is the main aging mechanism after the pipeline has been in service for 0-18 years. After 18 years in service, the pipeline shows a decrease in elongation at break by 16.2%. The oxidation induction time of the pipeline is 25.7 minutes, which is 28.5% higher than the national standard value. The findings from this study provide reference data and theoretical guidance for the aging process study of buried polyethylene pipelines.
Article
Environmental Sciences
Ling Shang, Xiaofei Li, Haifeng Shi, Feng Kong, Ying Wang, Yizi Shang
Summary: This paper presents a nested approach for generating long-term, medium-term, and short-term reservoir scheduling models based on the actual needs of the Three Gorges-Gezhouba cascade reservoirs. The study also introduces various solving algorithms used in the multi-time scale coordinated and optimized scheduling model and compares their performance. The results show that the proposed models have better efficiency and good convergence, achieving maximization of the power generation benefits without violating any scheduling regulations.
Article
Multidisciplinary Sciences
Asmaa Ahmed Awad, Ahmed Fouad Ali, Tarek Gaber
Summary: The author proposed an improved version of the Long Short-Term Memory (ILSTM) algorithm by integrating particle swarm optimization (PSO) and chaotic butterfly optimization algorithm (CBOA) to optimize the weights of LSTM and improve the accuracy of intrusion detection system. Experimental results showed that ILSTM outperformed the original LSTM and other deep learning algorithms in terms of accuracy and precision.
Article
Engineering, Multidisciplinary
Zhongyuan Liang, Mei Liu, Peisi Zhong, Chao Zhang, Xiao Wang
Summary: A hybrid algorithm combining genetic algorithm and simulated annealing was studied for the complex multiproduct scheduling problem with 0-wait constraint. Improvement on initial population quality was achieved through DSM and three optimization strategies were proposed. The decoding process was successfully implemented, and the effectiveness of the algorithm was verified on related examples.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Management
F. Hooshmand, F. Mirarabrazi, S. A. MirHassani
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2020)
Article
Computer Science, Interdisciplinary Applications
F. Hooshmand, F. Amerehi, S. A. MirHassani
COMPUTERS & OPERATIONS RESEARCH
(2020)
Article
Mathematics
Mohsen Tahernia, Sirous Moradi, Somaye Jafari
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
(2020)
Article
Computer Science, Artificial Intelligence
M. Dodge, S. A. MirHassani, F. Hooshmand
Summary: The paper presents a DNA computing algorithm based on the sticker model to solve the two-dimensional cutting stock problem (TDCSP), proving that the time complexity of this algorithm on DNA computers is polynomial, taking into account the number of small pieces and the dimensions of the main board.
Article
Construction & Building Technology
Amirhossein Fani, Amir Golroo, S. Ali Mirhassani, Amir H. Gandomi
Summary: The study aims to develop an optimization framework for network-level pavement maintenance and rehabilitation planning considering the uncertain nature of pavement deterioration and the budget with a multistage stochastic mixed-integer programming model. The proposed model can find the optimal plan feasible for all possible scenarios of uncertainty and optimize the expectation of the objective function.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2022)
Article
Operations Research & Management Science
S. Moradi, S. Jafari
Summary: This work establishes results regarding the existence of solutions for set-valued and single-valued equilibrium problems in real Hausdorff topological vector spaces. Generalizations of convexity and continuity conditions for set-valued mappings are introduced and applied to special dense subsets of the domain, leading to the existence of local dense solutions. The existence of global solutions is then proven under a condition weaker than semistrict quasiconvexity, specifically for noncooperative n-person games with assumptions on locally segment-dense subsets of each player's strategy set.
Article
Construction & Building Technology
Amirhossein Fani, Hamed Naseri, Amir Golroo, S. Ali Mirhassani, Amir H. Gandomi
Summary: This study proposes a multi-stage stochastic mixed-integer programming model to address the high-level complexity of large-scale pavement maintenance scheduling problems. The findings show that the introduced approach is capable of effectively handling uncertainty in maintenance and rehabilitation problems.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Javad Rezaei, Fatemeh Zare-Mirakabad, Seyed Ali MirHassani, Sayed-Amir Marashi
Summary: This paper discusses the critical node detection problem in network robustness design, proposing a new solution and verifying its effectiveness, as well as introducing a new exact algorithm to improve the solving efficiency.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Hardware & Architecture
Behrooz Farkiani, Bahador Bakhshi, S. Ali MirHassani, Tim Wauters, Bruno Volckaert, Filip De Turck
Summary: This paper studies the problem of deployment and reconfiguration of a set of chains with different priorities with the objective of maximizing the service provider's profit. It proposes a MILP formulation and two solving algorithms, showing that the proposed heuristic can find a feasible solution in at least 83% of simulation runs in less than 7 seconds. The exact algorithm achieves 25% more profit 8 times faster than state-of-the-art MILP solving methods.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2021)
Article
Computer Science, Interdisciplinary Applications
S. M. Mirhadi, S. A. MirHassani
Summary: This paper proposes a new algorithm for solving the linear Cardinality Minimization Problem by converting it to the sum-of-ratio problem and solving it with an optimization algorithm. The efficiency of the algorithm is demonstrated through numerical experiments.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Article
Engineering, Civil
Ahmadreza Ghaffari, Mahmoud Mesbah, Ali Khodaii, S. Ali MirHassani
Summary: This paper proposes a model to find the optimal transit priority scheme in a multimodal transportation network under uncertain demand. The model is formulated as a risk-based bi-level optimization problem and solved using an ant colony algorithm. Numerical results show that demand uncertainty has a significant impact on the solution, and the proposed model is applicable to realistic networks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Operations Research & Management Science
Neda Beheshti Asl, S. A. MirHassani, S. Relvas, F. Hooshmand
Summary: This paper presents an efficient decomposition-based heuristic to solve a new variant of the pipeline scheduling problem, considering the impact of flow-rate stability on energy consumption. By developing a new continuous-time mixed-integer nonlinear programming model and applying decomposition technique, the proposed method is able to generate near-optimal solutions and achieve more stable flow-rates.
OPERATIONAL RESEARCH
(2022)
Article
Operations Research & Management Science
M. N. Yarahmadi, S. A. MirHassani, F. Hooshmand
Summary: This paper presents a novel method, called the feasible-finder model (FFM), to find a high-quality feasible solution for 0-1 mixed-integer programming problems. By solving a sequence of linear programming problems using an efficient ratio programming method, FFM proves to provide feasible solutions for the original MIP problem. Additionally, a quality-controlling cut is generated and added in each iteration to improve the solution quality. Computational results on CORAL and MIPLIB instances confirm the effectiveness of this method.
OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
S. A. MirHassani, A. Khaleghi, F. Hooshmand
EURO JOURNAL ON TRANSPORTATION AND LOGISTICS
(2020)
Article
Engineering, Civil
F. Hooshmand, F. Amerehi, S. A. MirHassani
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
(2020)
