Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN ...Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.展开更多
Cancer patients in China navigate a complex and uneven insurance landscape,making plan choice critical for equitable financial protection.This study conducts a structured narrative review(2010-2025)of the Web of Scien...Cancer patients in China navigate a complex and uneven insurance landscape,making plan choice critical for equitable financial protection.This study conducts a structured narrative review(2010-2025)of the Web of Science,PubMed,CNKI,and Wanfang databases,focusing on empirical research on insurance plan choice,enrollment,or switching among cancer patients and their households in China.Two reviewers independently screened studies and extracted information on key determinants and identification strategies.The evidence converges on five main determinants:insurance literacy,health knowledge,prior coverage,financial capability,and policy promotion intensity(PPI).However,most studies are cross-sectional and descriptive,with inconsistent operationalization of determinants,weak or absent mediation tests for PPI,and limited coverage of rural,elderly,and low-literacy populations.Building on these gaps,we synthesize an evidence map,propose an operational PPI index,and highlight quasi-experimental opportunities(such as staggered NRDL updates and variation in local publicity efforts)to identify mechanisms and inform more inclusive,patient-centered insurance design in China.展开更多
Purpose–In this paper,two popular multiple-criteria decision-making(MCDM)methods with hesitant fuzzy logic approach;hesitant fuzzy analytic hierarchy process(hesitant F-AHP)and hesitant fuzzy the technique for order ...Purpose–In this paper,two popular multiple-criteria decision-making(MCDM)methods with hesitant fuzzy logic approach;hesitant fuzzy analytic hierarchy process(hesitant F-AHP)and hesitant fuzzy the technique for order preference by similarity to ideal solution(HF-TOPSIS)are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning(ERP)alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.Design/methodology/approach–Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues(i.e.time loss,increased costs and a loss of market share).On the other hand,finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.Findings–In this integrated approach,the hesitant F-AHP is used to determine the criteria weights,as the hesitant F-TOPSIS is utilized to rank ERP package alternatives.The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.Research limitations/implications–If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers,the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations.Therefore,the number of criteria and alternatives should be at reasonable numbers.Practical implications–The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.Originality/value–Furthermore,in literature,to the best of our knowledge,the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.展开更多
基金supported by the Ministry of Science and High Education of the Russian Federation by the grant 075-15-2022-1137supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R323),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.
文摘Cancer patients in China navigate a complex and uneven insurance landscape,making plan choice critical for equitable financial protection.This study conducts a structured narrative review(2010-2025)of the Web of Science,PubMed,CNKI,and Wanfang databases,focusing on empirical research on insurance plan choice,enrollment,or switching among cancer patients and their households in China.Two reviewers independently screened studies and extracted information on key determinants and identification strategies.The evidence converges on five main determinants:insurance literacy,health knowledge,prior coverage,financial capability,and policy promotion intensity(PPI).However,most studies are cross-sectional and descriptive,with inconsistent operationalization of determinants,weak or absent mediation tests for PPI,and limited coverage of rural,elderly,and low-literacy populations.Building on these gaps,we synthesize an evidence map,propose an operational PPI index,and highlight quasi-experimental opportunities(such as staggered NRDL updates and variation in local publicity efforts)to identify mechanisms and inform more inclusive,patient-centered insurance design in China.
文摘Purpose–In this paper,two popular multiple-criteria decision-making(MCDM)methods with hesitant fuzzy logic approach;hesitant fuzzy analytic hierarchy process(hesitant F-AHP)and hesitant fuzzy the technique for order preference by similarity to ideal solution(HF-TOPSIS)are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning(ERP)alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.Design/methodology/approach–Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues(i.e.time loss,increased costs and a loss of market share).On the other hand,finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.Findings–In this integrated approach,the hesitant F-AHP is used to determine the criteria weights,as the hesitant F-TOPSIS is utilized to rank ERP package alternatives.The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.Research limitations/implications–If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers,the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations.Therefore,the number of criteria and alternatives should be at reasonable numbers.Practical implications–The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.Originality/value–Furthermore,in literature,to the best of our knowledge,the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.
