Article
Computer Science, Interdisciplinary Applications
Duleabom An, Sophie N. Parragh, Markus Sinnl, Fabien Tricoire
Summary: This study presents a linear programming-based matheuristic for triobjective binary integer linear programming. By using lower bound and upper bound sets, the method generates a better approximation of the true Pareto front compared to existing methods on a large set of benchmark instances.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Energy & Fuels
Cristina C. B. Cavalcante, Cid C. de Souza, Celio Maschio, Denis Schiozer, Anderson Rocha
Summary: History matching is an important process in reservoir engineering to find models that can reproduce the performance of an actual reservoir by changing uncertain attributes. While progress has been made in history-matching approaches over the past two decades, finding alternative, efficient, and effective methodologies remains a research challenge due to the uniqueness of each reservoir.
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Islame F. C. Fernandes, Elizabeth F. G. Goldbarg, Silvia M. D. M. Maia, Marco C. Goldbarg
Summary: This study proposes a decomposition-based path-relinking method for multi-and many-objective combinatorial optimization problems. The proposed approach was compared with seven path-relinking techniques on three different combinatorial optimization problems, and a taxonomy for standardizing and classifying path generation strategies was proposed.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Carlos E. Andrade, Rodrigo F. Toso, Jose F. Goncalves, Mauricio G. C. Resende
Summary: This paper introduces a variant of the Biased Random-Key Genetic Algorithm that employs multiple parents and implicit path-relinking, providing complete independence between local search and problem definition. Computational experiments demonstrate performance benefits over traditional BRKGA and BRKGA with multiple parents, making intensification/diversification more natural and simplifying development efforts.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Industrial
Ankit Khare, Sunil Agrawal
Summary: This paper addresses the distributed permutation flowshop scheduling problem with the objective of minimizing total tardiness, a crucial aspect in today's customer-oriented market. Mixed-integer linear programming model, heuristics, and enhanced optimization algorithms were proposed and calibrated through experimental design to improve efficiency and demonstrate effectiveness. Benchmark results show the superiority of the presented algorithms in solving the problem.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Management
Daniel Cuellar-Usaquen, Camilo Gomez, David Alvarez-Martinez
Summary: This paper proposes a GRASP-based methodology for the TPP, which includes three constructive procedures and two local search operators. The method is enhanced with Path Relinking and Filtering strategies to improve performance and efficiency. Experimental results show competitive performance of this method in solving the traveling purchasing problem.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Thekra Al-douri, Mhand Hifi, Vassilis Zissimopoulos
Summary: This paper introduces an iterative algorithm to solve the max-min knapsack problem with multiple scenarios, consisting of construction, improvement, and destroying/repairing phases. The method remains competitive in providing high-quality solutions compared to recent algorithms available in the literature when evaluated on benchmark instances.
OPERATIONAL RESEARCH
(2021)
Article
Multidisciplinary Sciences
Eduardo Canale, Franco Robledo, Pablo Sartor, Luis Stabile
Summary: Students in MBA programs are divided into teams to promote diversity. This study introduces an approach for managing team grouping to achieve high diversity and minimize repetitions. By comparing different methods, the study finds that the heuristic algorithm outperforms other approaches in terms of diversity and repetition levels.
Article
Computer Science, Artificial Intelligence
Thia Aishwaryaprajna, Thia Kirubarajan, Ratnasingham E. Tharmarasa, Jonathan Rowe
Summary: A realistic problem of surveillance by UAV in the presence of weather factors, including cloud coverage and Gaussian noise, is defined. Recombination-based search mechanisms, specifically the univariate marginal distribution algorithm (UMDA), are proven effective in solving noisy combinatorial problems. This paper proposes a multi-objective UMDA (moUMDA) with diversification mechanisms for UAV surveillance, which provides more diverse and higher quality solutions compared to NSGA-II in solving this noisy problem, as shown by numerical simulations.
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION
(2023)
Article
Computer Science, Artificial Intelligence
Zhi-zhong Zeng, Zhi-peng Lue, Xin-guo Yu, Qing-hua Wu, Yang Wang, Zhou Zhou
Summary: This paper proposes a new learning method called post-flip edge-state learning (PF-ESL) for the max-cut problem. Unlike previous algorithms, PF-ESL focuses on edge-states as the critical information and extracts their statistics for learning. Experimental results show that PF-ESL is competitive and provides value-added learning for both the EDA perturbation operator and the path-relinking operator. The paper also introduces a new perspective on edge-states, which can inspire future research in learning-based algorithms and graph partitioning problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Marine
Karthikeyan Mayilvaganam, Anmol Shrivastava, Prabhu Rajagopal
Summary: This paper proposes a coverage path planner for autonomous vehicles used in inspection operations. The planner is based on a back and forth pattern and aims to generate a path with the least trajectory length and number of turns, covering the entire workspace. To overcome the challenges posed by concave vertices in arbitrary polygons, the paper proposes a tree search model based on polygon width and the back and forth pattern's sweep line. The model decomposes the input polygon in multiple ways, and the Dijkstra algorithm is used to obtain viable polygons with the least number of turns. The paper also proposes an ant colony optimization-based trajectory length optimizer to determine the polygon visiting order that minimizes trajectory length. The developed coverage path planner is versatile and applicable to any autonomous vehicle operating in a planar region.
Article
Chemistry, Multidisciplinary
Meilinda Fitriani Nur Maghfiroh, Vincent F. F. Yu, Anak Agung Ngurah Perwira Redi, Bayu Nur Abdallah
Summary: A substantial distribution system is achieved by designing the location facility and route generation simultaneously. This research combines the location routing problem (LRP) with time window constraints to solve the LRPTW problem using a combination of variable neighborhood search (VNS) and path relinking (PR).
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Mark W. Lewis, Amit Verma, Todd T. Eckdahl
Summary: Ribonucleic acid (RNA) molecules play essential roles in living cells, and predicting RNA structures and functionality involves solving the RNA folding problem through mathematical modeling, which can be achieved using a QUBO modeling paradigm and hybrid metaheuristic algorithm. Extensive testing results have shown a strong positive correlation with benchmark results.
JOURNAL OF HEURISTICS
(2021)
Article
Automation & Control Systems
Jianping Dou, Shuai Wang, Canran Zhang, Yunde Shi
Summary: In this paper, a novel path-relinking genetic algorithm (PR-GA) is proposed to solve the operation sequencing (OS) problem in Industry 4.0. The PR-GA finds the minimal-cost solution by recording feasible operation sequences and using designed crossover and mutation operations. It also establishes a new framework of GA that avoids tuning crossover and mutation rates.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Industrial
Martina Calzavara, Serena Finco, Daria Battini, Fabio Sgarbossa, Alessandro Persona
Summary: This paper proposes an innovative approach to solve the Joint Assembly Line Balancing and Feeding Problem, aiming to achieve integrated balancing and fully synchronized assembly-feeding system. By using the MILP model, it successfully reduces the number of assembly stations and inventory level, while avoiding workforce shortage issues in the feeding system.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Lixin Tang, Yun Dong, Jiyin Liu
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2015)
Article
Engineering, Industrial
Lixin Tang, Defeng Sun, Jiyin Liu
Article
Operations Research & Management Science
Lixin Tang, Feng Li, Jiyin Liu
NAVAL RESEARCH LOGISTICS
(2015)
Article
Engineering, Industrial
Jiaxiang Luo, Jiyin Liu, Yueming Hu
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2017)
Article
Management
Lixin Tang, Ying Meng, Zhi-Long Chen, Jiyin Liu
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2016)
Article
Computer Science, Artificial Intelligence
Lixin Tang, Yue Zhao, Jiyin Liu
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2014)
Article
Engineering, Industrial
Lixin Tang, Xie Xie, Jiyin Liu
Article
Engineering, Industrial
Lixin Tang, Wei Jiang, Jiyin Liu, Yun Dong
Article
Automation & Control Systems
Chang Liu, Lixin Tang, Jiyin Liu
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2020)
Article
Automation & Control Systems
Guodong Zhao, Jiyin Liu, Lixin Tang, Ren Zhao, Yun Dong
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2020)
Article
Automation & Control Systems
Lixin Tang, Xiangman Song, Jiyin Liu, Chang Liu
Summary: The Estimation of Distribution Algorithm (EDA) proposed in this article utilizes Kalman filtering and a learning strategy to address issues related to nonlinearity, variable coupling, and large-scale optimization problems. Computational experiments demonstrate the effectiveness of the algorithm. In practical applications, it has the potential to optimize process control parameters for continuous production processes like blast furnaces.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2021)
Article
Automation & Control Systems
Zuocheng Li, Lixin Tang, Jiyin Liu
Summary: This article proposes a memetic algorithm based on probability learning to solve the multidimensional knapsack problem (MKP), highlighting the problem-dependent heuristics and a novel framework. Experimental results demonstrate the effectiveness and practical values of the proposed method for MKP.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Pol Arias-Melia, Jiyin Liu, Rupal Mandania
Summary: This paper examines the problem of vehicle sharing and task allocation, proposing an integer programming model and a heuristic algorithm. Results show that sharing vehicles can save on vehicle usage and reduce carbon emissions.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Yizi Zhou, Anne Liret, Jiyin Liu, Emmanuel Ferreyra, Rupal Rana, Mathias Kern
ARTIFICIAL INTELLIGENCE XXXIV, AI 2017
(2017)
Article
Automation & Control Systems
Shuo Liu, Wen-Hua Chen, Jiyin Liu
INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING
(2016)