Article
Computer Science, Artificial Intelligence
Edukondalu Chappidi, Alok Singh
Summary: The anti-covering location problem (ACLP) is an NP-hard problem with important real-world applications. This paper proposes two evolutionary approaches based on genetic algorithm (GA) and discrete differential evolution (DDE) to solve the weighted version of ACLP. Computational results demonstrate the effectiveness of the proposed approaches.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Yongliang Lu, Una Benlic, Qinghua Wu
Summary: Covering Salesman Problem (CSP) is an extension of the Traveling Salesman Problem (TSP) with various real-life applications. A highly effective Hybrid Evolutionary Algorithm (HEA) is proposed to solve this NP-hard problem, surpassing current best-performing CSP heuristics on a large set of benchmark instances.
INFORMATION SCIENCES
(2021)
Article
Management
Amit Kumar Vatsa, Sachin Jayaswal
Summary: This study investigates the problem of assigning doctors to non-operational Primary Health Centers, considering clear guidelines on maximum population served and uncertainties in doctor availability. The robust capacitated multi-period maximal covering location problem with server uncertainty is formulated and solved efficiently using a Benders decomposition method, outperforming the CPLEX MIP solver significantly.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Edukondalu Chappidi, Alok Singh
Summary: This paper proposes a steady state genetic algorithm based approach to solve the obnoxious cooperative maximum covering location problem (OCMCLP) on a network. The proposed approach uses genetic operators and a local search strategy to improve the solutions obtained. Computational results show that the proposed approach outperforms existing state-of-the-art approaches for the OCMCLP.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Fazhan Zhang, Yichao He, Haibin Ouyang, Wenben Li
Summary: An enhanced group theory-based optimization algorithm (EGTOA) is proposed to solve the uncapacitated facility location problem (UFLP) quickly and effectively. By introducing a new local search operator and a redundant checking strategy, EGTOA outperforms existing algorithms in terms of solution quality and speed.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Economics
Salvador J. Vicencio-Medina, Yasmin A. Rios-Solis, Omar Jorge Ibarra-Rojas, Nestor M. Cid-Garcia, Leonardo Rios-Solis
Summary: This study focuses on the Maximal Covering Location Problem with Accessibility Indicators and Mobile Units, aiming to maximize facilities coverage, accessibility, and opportunities for inhabitants. A mixed-integer linear programming model is formulated, and a matheuristic approach combining exact and heuristic methods is proposed to solve larger instances. Experimental results demonstrate the efficiency of our methodologies in improving coverage and accessibility.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Yupeng Zhou, Mingjie Fan, Xiaofan Liu, Xin Xu, Yiyuan Wang, Minghao Yin
Summary: The mathematical formulation of the maximum weighted set k-covering problem is given for the first time in this paper, and a novel master-apprentice evolutionary algorithm is proposed to solve this problem. Experimental results show that the proposed algorithm performs the best among all competitors.
APPLIED INTELLIGENCE
(2023)
Article
Management
Marta Baldomero-Naranjo, Joerg Kalcsics, Alfredo Marin, Antonio M. Rodriguez-Chia
Summary: This study investigates the upgraded version of the maximal covering location problem with edge length modifications on networks. The problem focuses on locating facilities on network vertices to maximize coverage while considering the cost associated with reducing edge lengths within a given budget. This problem is classified as NP-hard on general graphs. To address this, the study proposes three different mixed-integer formulations and a preprocessing phase. Additionally, the proposed formulations are strengthened with valid inequalities and compared using performance tests on various datasets.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Mostafa Khatami, Amir Salehipour
Summary: The gradual minimum covering location problem with distance constraints (GMCLPDC) deals with locating undesirable facilities on a geographical map, considering a minimum distance between them. We propose a mixed-integer program and a threshold accepting heuristic to solve the problem. Computational experiments show the effectiveness of the heuristic in delivering quality solutions, outperforming the solver Gurobi.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Engineering, Industrial
Grzegorz Filcek, Jerzy Jozefczyk, Miroslaw Lawrynowicz
Summary: This study considers a joint location and scheduling problem involving selecting a number of executor locations and task plans. A heuristic algorithm Alg BC is proposed, utilizing the NSGA II scheme for multi-objective optimization. The performance of Alg BC is evaluated for small instances, and sensitivity analysis is provided for larger instances.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2021)
Article
Engineering, Environmental
Zhen Wang, Yongrui Duan, Jiazhen Huo
Summary: To address citizens' demand for returning recyclable waste, the Chinese government has introduced smart recycling facilities. This study focuses on how to properly allocate recycling infrastructure in an uncertain environment with limited smart recycling facilities. Mathematical formulations and solution procedures were validated through two application cases to maximize the coverage of demand.
WASTE MANAGEMENT & RESEARCH
(2021)
Article
Operations Research & Management Science
Robert Aboolian, Oded Berman, Majid Karimi
Summary: This paper discusses the design of a facility network with the goal of minimizing overall costs while taking congestion into account. The problem is formulated as a nonlinear mixed-integer program to determine the optimal facility selection and service rate assignment. Consumers aim to maximize utility when choosing facilities, ensuring no incentive to change choices in user-equilibrium. The nonlinear constraints are linearized to efficiently solve a mixed-integer linear problem.
TRANSPORTATION SCIENCE
(2022)
Article
Engineering, Civil
Chao Wang, Ziqiong Wang, Ye Tian, Xingyi Zhang, Jianhua Xiao
Summary: This paper proposes a multi-objective facility location problem under uncertainty of facilities and suggests the use of a dual-population based evolutionary algorithm to address the problem. Experimental results show that the proposed method can effectively improve location reliability and obtain higher quality optimal solutions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Soumen Atta, Priya Ranjan Sinha Mahapatra, Anirban Mukhopadhyay
Summary: The multi-objective MCLP with customers' preferences deals with maximizing the sum of customer demands and preferences covered by a fixed number of facilities. A Pareto-based multi-objective harmony search algorithm (MOHSA) is proposed to tackle this problem and outperforms the well-known NSGA-II in terms of computation time.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Sofien Boutaib, Maha Elarbi, Slim Bechikh, Carlos A. Coello Coello, Lamjed Ben Said
Summary: This research aims to address the uncertainty factor in detecting and identifying code smells by proposing an evolutionary approach, effectively dealing with uncertain class labels. The Bi-ADIPOK method proposed has shown high detection and identification performance, better handling label uncertainty and reducing false alarms, with good performance in both uncertain and certain data environments.
APPLIED SOFT COMPUTING
(2022)
Article
Geography
Alan T. Murray, Antonio Ortiz, Seonga Cho
Summary: Over the past two decades, statistics and analytics have increasingly influenced decision-making in professional and collegiate baseball, particularly in the strategic positioning of outfielders. This paper demonstrates the potential of location analytics in optimizing outfielder positioning, resulting in improved performance. By utilizing a location optimization model and analyzing collegiate ball-tracking data, the study shows that trade-off configurations of outfielders can lead to performance improvements ranging from 1 to 3%, offering a significant strategic advantage over the course of a season.
JOURNAL OF GEOGRAPHICAL SYSTEMS
(2022)
Article
Engineering, Civil
Hongchu Yu, Alan T. Murray, Zhixiang Fang, Jingxian Liu, Guojun Peng, Mohammad Solgi, Weilong Zhang
Summary: This study aims to optimize unmanned ship routes using geographical theory and methodologies to enhance the safety and efficiency of maritime transportation. Automatic collision avoidance and compliance with maritime traffic rules remain challenges, but the development of unmanned ships will promote the future growth of intelligent ports.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Agriculture, Multidisciplinary
Alan T. Murray, Richard L. Church, B. Amelia Pludow, Peter Stine
Summary: This paper presents a new spatial optimization model for delineating contiguous areas in land use planning. The model can simultaneously delineate single or multiple patches, meeting specific size and spatial distinctiveness requirements. An application of the model to a land management problem involving wildfire mitigation efforts by the USDA Forest Service is also presented.
JOURNAL OF LAND USE SCIENCE
(2022)
Article
Economics
Jiwon Baik, Alan T. Murray
Summary: This paper introduces a bi-objective strategic location problem that addresses access and coverage. It presents a new mathematical formulation that considers both access and coverage, as well as a solution algorithm to find optimal solutions. Application findings from several case studies show that this approach provides critical insights for real-time decision-making and contributes to planning, management, and policy development.
PAPERS IN REGIONAL SCIENCE
(2022)
Article
Computer Science, Information Systems
Seonga Cho, Alan T. Murray, Somayeh Dodge, Jiwon Baik
Summary: Siting decisions are critical to the success of a service system as they can affect access, logistics, supply chains, transportation, and other qualities. This paper proposes a bi-objective spatial optimization model that considers access and service coverage in site selection. It introduces a heuristic approach to solve the problem involving facility location in continuous space, where access and coverage are simultaneously considered.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Alan T. Murray, Richard L. Church
Summary: Land acquisition was defined as the selection of spatial planning units to form a contiguous area of desired size while optimizing objectives. The problem is to ensure spatial contiguity among selected units. Existing models are either computationally complex or rely on simplifying assumptions. A new model formulation is introduced, which can be solved by exact methods and accommodates any interpretation of land unit adjacency. The model can be applied to problems involving tens of thousands of planning units, as demonstrated in the application experience for fuel removal efforts by the U.S. Forest Service.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Geography
Alan T. Murray, Jiwon Baik
Summary: Spatial optimization with multiple objectives is complex, and open-source approaches offer potential for wider access and integration of GIScience methods. This article presents a bi-objective spatial problem as an example to illustrate the challenges and opportunities of open-source solutions. It discusses various solution approaches and their computational requirements, functionality, solution quality, and encountered issues. Empirical applications in emergency response, healthcare access, food processing, and strategic player positioning are detailed. This study highlights the capabilities, limitations, and challenges of open-source science in addressing multi-objective spatial optimization problems.
TRANSACTIONS IN GIS
(2023)
Article
Geography
Alan T. Murray, Susan Burtner
Summary: Physical distancing measures are essential in responding to pandemics, such as COVID-19, which is transmitted through interaction. This paper discusses the use of geographic information systems and spatial optimization to plan for physical distancing at micro-scales, enabling the resumption of social, economic, and entertainment activities. It also highlights applications for office space occupancy and room seating.
LETTERS IN SPATIAL AND RESOURCE SCIENCES
(2023)
Article
Health Care Sciences & Services
Sean C. Reid, Vania Wang, Ryan Assaf, Sofia Kaloper, Alan Murray, Steven Shoptaw, Pamina Gorbach, Susan Cassels
Summary: This study described the development and validation of a web-based activity space survey for collecting geographic information relevant to ending the HIV epidemic. The survey design team identified four themes through cognitive interviews: functionality of geospatial questions, representation and accessibility, privacy, and length and understanding of the survey. The ease of use and inclusion of familiar mapping tools improved accuracy and participation, while trust and inclusive language alleviated privacy concerns.
JMIR FORMATIVE RESEARCH
(2023)
Article
Environmental Sciences
B. Amelia Pludow, Alan T. Murray, Vanessa Echeverri, Richard L. Church
Summary: This paper examines the issue of balancing multiple objectives in forest treatment planning and evaluates the solution quality using a widely employed forest planning tool. The findings indicate that the obtained solutions are suboptimal and fail to fully represent the possible tradeoff range.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Geography
Huanfa Chen, Alan T. Murray, Rui Jiang
Summary: Location cover models are essential for efficiently providing services by siting facilities at demand points. Open-source tools have advantages in transparency and reproducibility, but the capabilities and limitations of these tools are still largely unknown, requiring further investigation and assessment.
JOURNAL OF GEOGRAPHICAL SYSTEMS
(2021)
Article
Geography
Alan T. Murray
Summary: This article explores the diversity of significance assessment methods in geographic spatial analysis, including considering different sampling perspectives. Some methods are based on comprehensive sampling, while others rely on fewer samples, making interpreting meaning challenging.
ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
(2021)
Article
Engineering, Civil
Hongchu Yu, Zhixiang Fang, Alan T. Murray, Guojun Peng
Summary: Maritime collision risk prediction is crucial for ocean transportation safety. This study proposes a novel space-time geographical approach to evaluate multi-ship near-miss collision risk, improving risk assessment and ship path optimization.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Environmental Studies
Alan T. Murray, Leila Carvalho, Richard L. Church, Charles Jones, Dar Roberts, Jing Xu, Katelyn Zigner, Deanna Nash
Summary: Communities like Santa Barbara, California may have advantages such as beaches and mountains, but they are also vulnerable to climate change, drought, wildfires, and floods. Recent events such as the Thomas fire and subsequent flooding in Montecito have highlighted the region's vulnerability to extreme weather conditions. This paper delves into the unique hazards and spatial analytics for assessing and predicting risks in the Santa Barbara region.
APPLIED SPATIAL ANALYSIS AND POLICY
(2021)
Review
Geography
Jing Xu, Alan Murray, Zifan Wang, Richard Church
TRANSACTIONS IN GIS
(2020)