As the global population ages rapidly, ensuring the accessibility of senior centers is crucial for supporting the well-being and quality of life of older adults. This study aims to address the facility location proble...
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As the global population ages rapidly, ensuring the accessibility of senior centers is crucial for supporting the well-being and quality of life of older adults. This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. The objective is to minimize travel distances for older adults while accounting for constraints such as mobility limitations and the existing distribution of senior centers. The elbow method is employed to identify the optimal number of new centers, balancing service accessibility and resource allocation. Open data sources, i.e., floating population and geographic information in Seoul, are used to estimate demand at various locations. The results show that adding up to 15 new centers in Seoul effectively reduced average travel distances for older adults by 24%, from 0.85 km to 0.64 km. The introduction of these new centers is prioritized based on their impact on the community, i.e., reducing travel distances and redistributing demand from overburdened facilities. These findings provide a data-driven framework for urban planners and policymakers to strategically enhance senior service networks in rapidly aging societies. By improving access to senior centers, this approach can help promote active aging, reduce social isolation, and ensure a better quality of life for older adults.
Context: Many heuristics-based indoor positioning approaches have been developed to enhance positioning estimation. However, there is no comprehensive survey of these heuristics information and methods. Objective: The...
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Context: Many heuristics-based indoor positioning approaches have been developed to enhance positioning estimation. However, there is no comprehensive survey of these heuristics information and methods. Objective: The main objective of this study is to provide a holistic view and an in-depth analysis of what heuristics information and methods have been used, their general achievements and limitations. This study aims to provide a comprehensive summary to facilitate further research on indoor positioning heuristics. Method: We conducted a systematic literature review (SLR) on indoor positioning heuristics. Results: Ninety-three (93) primary studies were selected. We found two general types of heuristics information and four primary heuristics methods, which we summarised in this paper. We also found that many of these positioning heuristics are tested in experimental settings only. Some heuristics claim practical applications but are not tested for the challenging and typical indoor environments. Conclusion: Most existing heuristics information and methods rely on the assumptions that may not be true in real life environment, hence limiting the usefulness of the positioning outcomes. Based on the analysis of this SLR, we propose two research directions to enhance positioning estimation.
Protecting communication networks against failures is becoming increasingly important as they have become an integrated part of our society. Cable failures are fairly common, but it is unacceptable for a single cable ...
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Protecting communication networks against failures is becoming increasingly important as they have become an integrated part of our society. Cable failures are fairly common, but it is unacceptable for a single cable failure to disconnect communication for more than a few seconds-hence protection schemes are employed. In contrast to manual intervention, automatic protection schemes such as shared backup path protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available today. In SBPP backup paths are planned in advance for every failure scenario in order to recover from failures quickly and efficiently. Planning SBPP is an NP-hard optimization problem, and previous work confirms that it is time-consuming to solve the problem in practice using exact methods. We present heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than was achieved for 5 of 7 benchmark instances (and a gap of less than for the remaining instances.).
Scaling the CMOS devices deep into the nanorange reduces their reliability margins significantly. Consequently, accurately calculating the reliability of digital nanocircuits is becoming a necessity for investigating ...
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Scaling the CMOS devices deep into the nanorange reduces their reliability margins significantly. Consequently, accurately calculating the reliability of digital nanocircuits is becoming a necessity for investigating design alternatives to optimize the trade-offs between area-power-delay and reliability. However, accurate reliability calculation of large and highly connected circuits is complex and very time consuming. This paper proposes a progressive consensus-based algorithm for identifying the worst reliability input vectors and the associated critical logic gates. Improving the reliability of the critical gates helps circuit designers to effectively improve the circuit overall reliability while having a minimal impact on the traditional power-area-deal design parameters. The accuracy and efficiency of the algorithm can be tuned to fit a variety of applications. The algorithm scales well with circuit size, and is independent of the interconnect complexity and the logic depth. Extensive computational results show that the accuracy and the efficiency of the proposed algorithm are better than the most recent results reported in the literature.
Fuzzy Optimization models and methods has been one of the most and well studied topics inside the broad area of Soft Computing. Particularly relevant is the field of fuzzy linear programming (FLP). Its applications as...
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Fuzzy Optimization models and methods has been one of the most and well studied topics inside the broad area of Soft Computing. Particularly relevant is the field of fuzzy linear programming (FLP). Its applications as well as practical realizations can be found in all the real world areas. As FLP problems constitute the basis for solving fuzzy optimization problems, in this paper a basic introduction to the main models and methods in FLP is presented and, as a whole, Linear Programming problems with fuzzy costs, fuzzy constraints and fuzzy coefficients in the technological matrix are analyzed. But fuzzy sets and systems based optimization methods do not end with FLP, and hence in order to solve more complex optimization problems, fuzzy sets based Meta-heuristics are considered, and two main operative approaches described. Provided that these techniques obtain efficient and/or effective solutions, we present a fuzzy rule based methodology for coordinating Meta-heuristics and in addition, to provide intelligence, we propose a process of extraction of the knowledge to conduct the coordination of the system.
Considering the restriction of optimal profit realizing due to capital constraints in the perishable supply chain, this paper discusses two financing models, crowdfunding financing and bank credit financing from the s...
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Considering the restriction of optimal profit realizing due to capital constraints in the perishable supply chain, this paper discusses two financing models, crowdfunding financing and bank credit financing from the small-medium enterprise (SME) bank, for the dynamic ordering and pricing system of perishable goods in zero-inventory under capital constraints. heuristics algorithms are designed to solve the model. In dynamic crowdfunding financing, retailers bear different demand for capital in different periods and the capital gap for the retailer will narrow over time. In the SME financing model, the requirement for capital depends on retail size. We characterize the conditions of the financing preference between crowdfunding and SME financing channel. Smaller retailers, relative to the bigger players, are more willing to assure higher financing returns to gain the investment.
Recently, the adaptability of production systems is crucial for various facilities or departments, focusing on minimizing the cost associated with material flow in facility layout problems. To address these challenges...
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Recently, the adaptability of production systems is crucial for various facilities or departments, focusing on minimizing the cost associated with material flow in facility layout problems. To address these challenges, an examination of dynamic problems becomes imperative. This paper presents a mathematical model designed explicitly for dynamic facility layout problems (DFLP) characterized by fixed shapes and unequal areas. The model incorporates input and output points, allowing flexibility in their placement within facilities, and treats material handling system input/output (I/O) points as decision variables. The proposed approach utilizes an Improved Particle Swarm Optimization algorithm (IPSO) and an Improved Genetic Algorithm (IGA) to solve the resulting mixed integer nonlinear programming (MINLP) model. Both a theoretical problem and a real-world case are employed to assess the effectiveness of the suggested algorithms. The outcomes demonstrate that the proposed algorithm outperforms the compared algorithms in identifying optimal solutions.
This paper work deals with the study of interest in the fields of Steganography and Steganalysis with the image, audio or video stego media against the corresponding cover media (without the hidden information) and un...
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In this research article, a hybrid approach is presented which based on well-known meta-heuristics algorithms. This study based on integration of Quantum Genetic Algorithm (QGA) and Estimation of Distribution Algorith...
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ISBN:
(纸本)9781628411867
In this research article, a hybrid approach is presented which based on well-known meta-heuristics algorithms. This study based on integration of Quantum Genetic Algorithm (QGA) and Estimation of Distribution Algorithm, EDA, (for simplicity we use Q-EDA) for flowshop scheduling, a well-known NP hard Problem, while focusing on the total flow time minimization criterion. A relatively new method has been adopted for the encoding of jobs sequence in flowshop known as angel rotations instead of random keys, so QGA become more efficient. Further, EDA has been integrated to update the population of QGA by making a probability model. This probabilistic model is built and used to generate new candidate solutions which comprised on best individuals, obtained after several repetitions of proposed (Q-EDA) approach. As both heuristics based on probabilistic characteristics, so exhibits excellent learning capability and have minimum chances of being trapped in local optima. The results obtained during this study are presented and compared with contemporary approaches in literature. The current hybrid Q-EDA has implemented on different benchmark problems. The experiments has showed better convergence and results. It is concluded that hybrid Q-EDA algorithm can generally produce better results while implemented for Flowshop Scheduling Problem (FSSP).
In future smart transmission grids, there are distributed applications that will benefit from the deployment of Internet Protocol (IP) multicast technology for communication. Sharing of Routable-Sample Values (R-SV) a...
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In future smart transmission grids, there are distributed applications that will benefit from the deployment of Internet Protocol (IP) multicast technology for communication. Sharing of Routable-Sample Values (R-SV) and Routable-GOOSE among the digital substations for wide-area monitoring, protection, and control (WAMPAC) applications will be needed. Using multicast for distribution of R-SVs is resource-efficient and offers a simpler configuration with only the interested substations needing reconfiguration. However, the demands for such concurrent delivery of R-SV data will put constraints on the underlying supporting networking infrastructure. For example, it must be ensured that the paths taken to route data traffic are within the bounds of delay to achieve the aims of the WAMPAC application. In this paper, we look at the problem of network topology augmentation through link additions. We present a heuristic algorithm that finds a set of links to be added to a network topology such that the multicast distribution tree for a multicast configuration is bounded by latency, which is set as the hop-count threshold. Our results show that by adding a few new links to the network topology, the delay incurred by the multicast traffic from sources to destinations can be reduced.
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