Article
Mathematics, Applied
Marina A. Medvedeva, Vasilios N. Katsikis, Spyridon D. Mourtas, Theodore E. Simos
Summary: In this paper, the knapsack problem is transformed into the TV-ILP problem, presenting an online solution to the RTVKP combinatorial optimization problem and emphasizing the limitations of static methods. The RTVKP is also utilized in finance and tested with real-world data sets to demonstrate it as an excellent alternative to traditional approaches.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Benson Shu Yan Lam, Alan Wee-Chung Liew
Summary: This paper proposes a BQP solver that alternates between deterministic search and stochastic neighborhood search to tackle large BQP problems. Experimental results demonstrate that the proposed solver outperforms other methods in terms of solution quality and computational complexity.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Automation & Control Systems
Daniel Arnstrom, Daniel Axehill
Summary: In model-predictive control, it is important to efficiently solve optimization problems and have upper bounds on worst-case solution time. We propose an algorithm to compute the sequence of subproblems that an active-set algorithm solves and set worst-case bounds on iteration count and solution time. The usefulness of our method is illustrated on a set of quadratic program problems.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Interdisciplinary Applications
Xiangjing Lai, Jin-Kao Hao, Zhang-Hua Fu, Dong Yue
Summary: The capacitated clustering problem is a general model relevant for a variety of important applications. This work presents an original and highly effective algorithm for solving this problem, which significantly outperforms existing state-of-the-art algorithms in the literature. The key feature of the algorithm, combining neighborhood decomposition-driven local search with perturbation, can be useful for designing effective heuristic algorithms for other important clustering problems.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Joaquin Pacheco, Silvia Casado
Summary: The COVID-19 pandemic in 2020 caused a shortage of important supplies in healthcare systems. Volunteers used 3D printers to manufacture face shields and organizations were responsible for transportation. This study aims to develop an efficient system for planning and rationalizing these activities.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Shaowen Lan, Wenjuan Fan, Shanlin Yang, Panos M. Pardalos
Summary: This paper studies an integrated physician planning and scheduling problem, proposes an integer programming model, and uses a Variable Neighborhood Search algorithm to obtain high-quality solutions. The algorithm performs superiorly in experiments, outperforming other compared algorithms.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Operations Research & Management Science
Jacek Gondzio, E. Alper Yildirim
Summary: This paper investigates how to reformulate a standard quadratic program as a mixed integer linear programming problem, proposing two alternative formulations. By utilizing binary variables and valid inequalities, the formulations significantly outperform other global solution approaches in extensive computational results.
JOURNAL OF GLOBAL OPTIMIZATION
(2021)
Article
Computer Science, Software Engineering
Bo Hu, Hui Xiao, Nan Yang, Hao Jin, Lei Wang
Summary: The study focused on portfolio optimization with cardinality constraint, using double roulette wheel selection and quadratic programming to determine assets and proportions, with accuracy improved through local search. Experimental results demonstrated the algorithm's superior efficiency and accuracy compared to existing methods, showing that tailored algorithms can enhance computational efficiency but may require adjustments for different problems.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Operations Research & Management Science
Yangming Zhou, Yawen Kou, MengChu Zhou
Summary: This paper addresses a soft-clustered vehicle routing problem by partitioning customers into clusters and ensuring that all customers within a cluster are served by the same vehicle. It presents an efficient bilevel memetic search method that outperforms existing algorithms in terms of solution quality and computation time.
TRANSPORTATION SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Soukaina Oujana, Lionel Amodeo, Farouk Yalaoui, David Brodart
Summary: This paper discusses a research project that aims to optimize the scheduling of production orders in the packaging field. The problem is modeled as an extended version of the hybrid and flexible flowshop scheduling problem with precedence constraints, parallel machines, and sequence-dependent setups. Two methodologies, mixed-integer linear programming (MILP) and constraint programming (CP), are used to tackle the problem. Resource calendar constraints are added to the models, and a novel heuristic is designed for quick solutions. The proposed problem can be easily modified to suit real-world situations involving similar scheduling characteristics.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Yangming Zhou, Jin-Kao Hao, Beatrice Duval
Summary: This paper presents frequent pattern-based search method that combines data mining and optimization. The method emphasizes the relevance of a modular- and component-based approach and demonstrates its application to the quadratic assignment problem.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Christophe Wilbaut, Raca Todosijevic, Said Hanafi, Arnaud Freville
Summary: The discounted {0,1} knapsack problem (D{0-1}KP) is a variant of the well-known knapsack problem where items are partitioned into groups and a discount relationship is introduced among items in each group. In this work, a new variable neighborhood search (VNS) algorithm is proposed to solve the D{0-1}KP, and several greedy heuristics are used to build initial feasible solutions. The performance of VNS is evaluated and compared with state-of-the-art metaheuristics, demonstrating its robustness and competitiveness.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Information Systems
Wang Li, Senhao Jiang, Miaoxin Jin
Summary: This paper proposes a multi-objective method for speed curve optimization in heavy haul train operation, achieving energy conservation, punctuality, and smoothness through an optimization model and a weight selection algorithm.
Article
Management
Guillaume Derval, Pierre Schaus
Summary: The Maximal-Sum Submatrix problem maximizes the sum of entries in a subset of rows and columns from an original matrix. Despite being NP-hard, it has practical applications in data mining. State-of-the-art results have been achieved by combining Constraint Programming with custom algorithms, but this study introduces new upper bounds and pruning algorithms to further improve the approach, showing better performance on both synthetic and real-life data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Mathematics, Applied
Arezu Zare
Summary: This paper proposes a solution to the complex quadratic double-ratio minimax optimization problem and evaluates the efficiency of the algorithm through numerical examples.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2023)
Article
Engineering, Industrial
Haibo Wang, Bahram Alidaee, Jaime Ortiz, Wei Wang
Summary: This study proposes solutions for multi-skilled workforce management in seasonal business operations through mixed-integer programming models and heuristic methods, addressing the problem of task assignment for workers with different skills.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Review
Management
Bahram Alidaee, Haitao Li, Haibo Wang, Keith Womer
Summary: This paper discusses scheduling with arbitrary due dates and no idle time permitted between jobs, aiming to minimize the total earliness and tardiness. Mathematical programming formulations for single and parallel machine problems with fixed and controllable processing and setup times are reviewed, weaknesses are identified, corrections/improvements are provided, and further research directions are suggested.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Yu Du, Gary Kochenberger, Fred Glover, Haibo Wang, Mark Lewis, Weihong Xie, Takeshi Tsuyuguchi
Summary: Finding good solutions to clique partitioning problems is computationally challenging. The choice of modeling structure has a significant impact on obtaining practical solutions from exact solvers. Commercial solvers like CPLEX, GUROBI, and XPRESS combined with the right model can greatly improve solution computation for modest-sized problems. This paper explores and compares the use of three commercial solvers on clique partitioning problems and finds that the quadratic model outperforms the classic linear model as problem size increases.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Article
Green & Sustainable Science & Technology
Wei Wang, Haibo Wang, Jaime Ortiz, Bahram Alidaee, Bowen Sun
Summary: This study uses a causal analytic framework to evaluate the effectiveness of government policy on the reduction of industrial pollutants in 284 Chinese cities between 2005 and 2016. The results show that city government policies, economic power, the influence of megacities, and geographical region significantly affect industrial pollution reduction, with economic power having a significant interaction with city government policies. The study also finds long-term causality among industrial pollution reduction, fixed assets investment, and GDP per-capita in city, urban agglomeration, and regional levels.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Bowen Sun, Haibo Wang, Jaime Ortiz, Jun Huang, Can Zhao, Zelang Wang
Summary: This paper discusses the issue of urban sustainable development in China. By introducing the slack-based measure, a network data envelopment analysis model is proposed to analyze the eco-efficiency of 284 Chinese cities and explore the role of local government in providing public service and improving social well-being. The results show a significant decrease in eco-efficiency of Chinese cities from 2005 to 2016, mainly attributed to the distribution and consumption processes. The study compares these results with an existing index system and reveals structural differences between cities.
Article
Business, Finance
Wei Wang, Jun Huang, Haibo Wang, Bahram Alidaee
Summary: This study examines the efficiency of US community banks and identifies the factors influencing it. The findings show that bank size, community size, and unemployment rate have a positive relationship with efficiency, while relative community affluence has a negative relationship. Additionally, community banks offering real estate loans or diversifying their loan services perform better than those focusing on agricultural loans.
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
(2022)
Article
Industrial Relations & Labor
Md Farid Talukder, Haibo Wang
Summary: This study aims to analyze the impact of stock options on talent retention and knowledge productivity in knowledge intensive firms. The results indicate that stock options significantly affect knowledge worker retention and financial performance, especially during the pandemic. Firm innovation also has a significant impact on financial performance, particularly during the pandemic. However, knowledge worker retention does not have a significant impact on firm innovation and financial performance.
INTERNATIONAL JOURNAL OF MANPOWER
(2023)
Article
Computer Science, Interdisciplinary Applications
Haibo Wang, Bahram Alidaee
Summary: In this study, a hybrid-heuristic algorithm is designed by combining key components of three well-known meta-heuristics, and applied to large-scale quadratic assignment problem. The algorithm provides an efficient approach to the problem and has the potential to adapt to a wide range of problems.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Wei Wang, Haibo Wang, Jun Huang, Huijun Yang, Jiefang Li, Qinglan Liu, Zelang Wang
Summary: This study examines the spillover effects of megacities on regional industrial pollution reduction in urban agglomerations in China. The results show that infrastructure investment indicators at the megacity and urban agglomeration levels have short-term spillover effects on surrounding cities for dust reduction, but not for sulfur dioxide reduction. However, substantial spatial spillover effects were found over the long term at both the city and urban agglomeration levels.
Article
Computer Science, Interdisciplinary Applications
Yang Wang, Haichao Liu, Bo Peng, Haibo Wang, Abraham P. Punnen
Summary: This paper proposes a multi-day task assignment model with many variables and constraints, which is computationally challenging. An innovative three-phase matheuristic algorithm is introduced to solve this problem, which outperforms other existing algorithms in terms of solution quality and computational time. Experimental analysis is conducted to identify the key components contributing to the superior performance of the proposed algorithm.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Economics
Haibo Wang, Bahram Alidaee
Summary: White-Glove Service (WGS) is an emerging business model that combines omnichannel retailing, demand-driven supply chain, and crowdsourcing by a multiskilled workforce. It aims to meet the expectations of customers for convenience, speed, consistency, and personalized service.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Education, Scientific Disciplines
Teng Tong, Jaime Ortiz, Haibo Wang
Summary: This paper revisits the causal links between financial development, coal consumption, and CO2 emissions in P.R. China over the 1977-2017 period to validate the development of its natural gas industry. The results show that there are no long-run relationships among these three variables, but there is a Granger causality between coal consumption and CO2 emissions, and a one-way Granger causality from financial development to both coal consumption and CO2 emissions. These findings have important policy implications for the Chinese government's efforts to achieve carbon neutrality.
Proceedings Paper
Automation & Control Systems
Bahram Alidaee, Haibo Wang
Summary: In this paper, the uncapacitated location problem with a restriction on the number of facilities is addressed. A hybrid algorithm combining genetic algorithm and tabu search is proposed for solving this problem. The effectiveness of the algorithm is tested on benchmark problems and compared with a leading algorithm based on GRASP.
Article
Computer Science, Information Systems
Haibo Wang, Wendy Wang, Yi Liu, Bahram Alidaee
Summary: Machine learning is increasingly used in fraud detection, but the highly imbalanced data makes it challenging and calls for approaches beyond traditional methods. This study proposes a framework for fraud detection using quantum machine learning with evaluation on two datasets, showing the potential of quantum machine learning on time series data and the merit of traditional machine learning approaches on non-time series data.
Article
Computer Science, Information Systems
Wei Wang, Haibo Wang, Bahram Alidaee, Jun Huang, Huijun Yang
Summary: Smart grid construction provides basic conditions for the grid connection of renewable energy sources, but the integration of large-scale intermittent renewable energy sources increases the complexity of power system operation, requiring optimization and integration to ensure flexibility and stability. Dividing the smart grid into logical clusters helps overcome challenges caused by the grid connection of intermittent renewable energy sources.
