• Management Science and Financial Engineering
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• v.14 no.2
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• pp.45-66
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• 2008

Refuse collection, one of important elements in reverse logistics, is an activity rendering recyclables or wastes and moving them to some points where further treatment is required. Among various decisions in the collection activity, we focus on network design, which is the problem of locating collection points as well as allocating refuses at demand points to collection points while satisfying the capacity restriction at each collection point. Here, the collection point is the place where recyclables or wastes near the point are gathered, and locating the collection points is done by selecting them from a given set of potential sites. The objective is to minimize the sum of fixed costs to open collection points and transportation costs to move refuses from demand points to collection points. An integer programming model is developed to represent the problem mathematically and due to the complexity of the problem, two types of heuristics, one with simultaneous and the others with separate location and allocation, are suggested. Computational experiments were done on test problems up to 500 potential sites, and the results are reported. In particular, some heuristics gave near optimal solutions for small-size test problems, i.e., 2% gaps in average from the optimal solution values.

• Management Science and Financial Engineering
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• v.19 no.2
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• pp.19-29
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• 2013

Refuse collection network design, one of major decision problems in reverse logistics, is the problem of locating collection points and allocating refuses at demand points to the opened collection points. As an extension of the previous models, we consider capacity and maximum allowable distance constraints at each collection point. In particular, the maximum allowable distance constraint is additionally considered to avoid the impractical solutions in which collection points are located too closely. Also, the additional distance constraint represents the physical distance limit between collection and demand points. The objective is to minimize the sum of fixed costs to open collection points and variable costs to transport refuses from demand to collection points. After formulating the problem as an integer programming model, we suggest an optimal branch and bound algorithm that generates all feasible solutions by a simultaneous location and allocation method and curtails the dominated ones using the lower bounds developed using the relaxation technique. Also, due to the limited applications of the optimal algorithm, we suggest two heuristics. To test the performances of the algorithms, computational experiments were done on a number of test instances, and the results are reported.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.202.2-202.2
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• 2003

• IE interfaces
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• v.20 no.1
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• pp.58-68
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• 2007

This research deals with a vehicle scheduling problem for the sludge collection strategies which might be solved via quantitative analysis and cost evaluations schemes. This problem can be modeled as a kind of capacitated vehicle routing pick-up problems. With the aim of establishing operation schedule of vehicles and analyzing the total cost under considering various assumptions and realistic restrictions of the sludge collection problem, we propose a heuristic method based on the genetic algorithm in conjunction with the sweep algorithm and the 4-opt algorithm. Finally, we present the cost effective operation schedule that can be used as the managing tool for the sludge treatment plant of the multi-purpose dam.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.351-355
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• 2023

The need for Advanced LOSA arises from the limitations and drawbacks of traditional LOSA. Amended LOSA aims to address some of the shortcomings of the original methodology and make it more effective and relevant to current aviation safety needs. Some of the key reasons for developing Advanced LOSA include Enhancing the scope, Improving data collection and analysis, Providing more targeted safety recommendations. First, Traditional LOSA mainly focuses on flight deck operations, but Advanced LOSA expands the scope to include other operational areas such as cabin operations, ground handling, and maintenance. Second, Advanced LOSA can build a Forecasting System that can predict the future through data collection and data analysis. Third, Advanced LOSA aims to provide more specific and targeted safety recommendations based on the Aviation data collection and Aviation data analysis. Overall, Advanced LOSA seeks to improve aviation safety by addressing the limitations of traditional LOSA and providing a more comprehensive and effective methodology for identifying and mitigating safety risks in aviation operations.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.187-192
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• 2023

The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.319-322
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• 2019

There are many techniques for locating users in an indoor spot. Among them, WiFi fingerprinting technique which is widely used is phased into a data collection step and a positioning step. In the data collection step, all surrounding Wi-Fi signals are collected and managed as a list. The more data collected, the better the accuracy of the indoor position based on Wi-Fi fingerprint. Existing high-quality data collection and management methods are time consuming and costly, and many operations are required to extract and generate data necessary for machine learning. Therefore, we research how to collect and manage large amount of data in limited resources. This paper presents efficient data collection methods and data generation for learning.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.730-739
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• 2005

A common problem encountered in product or process design is the selection of optimal parameter levels which involve simultaneous consideration of multiresponse variables. A multiresponse problem is solved through three major stages: data collection, model building, and optimization. To date, various methods have been proposed for the optimization stage, including the desirability function approach and loss function approach. In this paper, we first propose a framework classifying the existing studies and then propose some promising directions for future research.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.350-353
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• 1998

Recently, local governments have started projects of implementing Geographic Information Systems (GIS) as an infrastructure for the collection, storage, and analysis of the spatial information. So far, these projects have been approached from the areas such as the civil engineering and the computer science perspectives. Nonetheless, in order for a GIS project to be successful, it should be approached from the management perspectives as well. In this paper, the authors discusses about the management issues such as the determination of priority of the sub-projects, the organizational structure that takes charge of the project and the evaluation of the performance of the project.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.182-185
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• 1996

This paper analyzes how the international callback services affect on the international telecommunications market. We present a simple game-theoretic model to compare the equilibrium outcomes before and after the arrival of callback operator. We find that the callback service arises from the inefficiencies in the national telecommunications market and the accounting rate system between international telecommunications carriers. Also, we identify the conflicting interests among the governments and carriers, by examining how the callback service affects the collection rate, quantities demanded, carrier's profit and social welfare of each country.