| 1. |
- Pan, S, et al.
(författare)
-
A study on influential factors of occupant window-opening behavior in an office building in China
- 2018
-
Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323 .- 1873-684X. ; 133, s. 41-50
-
Tidskriftsartikel (refereegranskat)abstract
- Occupants often perform many types of behavior in buildings to adjust the indoor thermal environment. In these types, opening/closing the windows, often regarded as window-opening behavior, is more commonly observed because of its convenience. It not only improves indoor air quality to satisfy occupants' requirement for indoor thermal comfort but also influences building energy consumption. To learn more about potential factors having effects on occupants' window-opening behavior, a field study was carried out in an office building within a university in Beijing. Window state (open/closed) for a total of 5 windows in 5 offices on the second floor in 285 days (9.5 months) were recorded daily. Potential factors, categorized as environmental and non-environmental ones, were subsequently identified with their impact on window-opening behavior through logistic regression and Pearson correlation approaches. The analytical results show that occupants' window-opening behavior is more strongly correlated to environmental factors, such as indoor and outdoor air temperatures, wind speed, relative humidity, outdoor FM2.5 concentrations, solar radiation, sunshine hours, in which air temperatures dominate the influence. While the non-environmental factors, i.e. seasonal change, time of day and personal preference, also affects the patterns of window-opening probability. This paper provides solid field data on occupant window opening behavior in China, with high resolutions and demonstrates the way in analyzing and predicting the probability of window-opening behavior. Its discussion into the potential impact factors shall be useful for further investigation of the relationship between building energy consumption and window-opening behavior.
|
|
| 2. |
- Cai, Demin, et al.
(författare)
-
Epigenetic and SP1-mediated regulation is involved in the repression of galactokinase 1 gene in the liver of neonatal piglets born to betaine-supplemented sows
- 2017
-
Ingår i: European Journal of Nutrition. - : Springer Science and Business Media LLC. - 1436-6207 .- 1436-6215. ; 56:5, s. 1899-1909
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: In this study, we sought to investigate the effects of maternal betaine supplementation on the expression and regulation of GALK1 gene in the liver of neonatal piglets.Methods: Sixteen sows of two groups were fed control or betaine-supplemented diets (3 g/kg), respectively, throughout the pregnancy. Newborn piglets were individually weighed immediately after birth, and one male piglet close to mean body weight from the same litter was selected and killed before suckling. Serum samples of newborn piglets were analyzed for biochemical indexes, hormone and amino acid levels. Liver samples were analyzed for GALK1 expression by real-time PCR and western blotting, while GALK1 regulational mechanism was analyzed by methylated DNA immunoprecipitation, chromatin immunoprecipitation and microRNAs expression.Results: Betaine-exposed neonatal piglets had lower serum concentration of galactose, which was associated with significantly down-regulated hepatic GALK1 expression. The repression of GALK1 mRNA expression was associated with DNA hypermethylation and more enriched repression histone mark H3K27me3 on its promoter. Binding sites of SP1, GR and STAT3 were predicted on GALK1 promoter, and decreased SP1 protein content and lower SP1 binding to GALK1 promoter were detected in the liver of betaine-exposed piglets. Furthermore, the expression of miRNA-149 targeting GALK1 was up-regulated in the liver of betaine-exposed piglets, along with elevated miRNAs-processing enzymes Dicer and Ago2.Conclusions: Our results suggest that maternal dietary betaine supplementation during gestation suppresses GALK1 expression in the liver of neonatal piglets, which involves complex gene regulation mechanisms including DNA methylation, histone modification, miRNAs expression and SP1-mediated transcriptional modulation.
|
|
| 3. |
- Carling, Kenneth, et al.
(författare)
-
An empirical test of the gravity p-median model
- 2012
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.
|
|
| 4. |
- Carling, Kenneth, et al.
(författare)
-
Distance measure and the p-median problem in rural areas
- 2012
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.
|
|
| 5. |
- Carling, Kenneth, et al.
(författare)
-
Distance measure and the p-median problem in rural areas
- 2015
-
Ingår i: Annals of Operations Research. - : Springer. - 0254-5330 .- 1572-9338. ; 226:1, s. 89-99
-
Tidskriftsartikel (refereegranskat)abstract
- The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region with a sparse, heterogeneous network and a non-symmetric distribution of the population. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (1-100 facilities). We find that the network distance give as good a solution as the travel-time network. The Euclidean distance gives solutions some 4-10 per cent worse than the network distances, and the solutions tend to deteriorate with increasing P. Our conclusions extend to intra-urban location problems.
|
|
| 6. |
- Carling, Kenneth, et al.
(författare)
-
Does Euclidean distance work well when the p-median model is applied in rural areas?
- 2012
-
Ingår i: Annals of Operations Research. - : Springer Science and Business Media LLC. - 0254-5330 .- 1572-9338. ; 201:1, s. 83-97
-
Tidskriftsartikel (refereegranskat)abstract
- The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. However, we find that the location of multiple hospitals in a rural region of Sweden with anon-symmetrically distributed population is quite sensitive to distance measure, and somewhat sensitive to spatial aggregation of demand points.
|
|
| 7. |
- Carling, Kenneth, et al.
(författare)
-
GRASP and statistical bounds for heuristic solutions to combinatorial problems
- 2016
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few metaheuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds has previously been found reliable when obtained from the Genetic algorithm whereas in this work they found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.
|
|
| 8. |
- Carling, Kenneth, et al.
(författare)
-
Measuring CO2 emissions induced by online and brick-and-mortar retailing
- 2014
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products.
|
|
| 9. |
- Carling, Kenneth, et al.
(författare)
-
Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing
- 2015
-
Ingår i: Transportation Research Part D. - : Elsevier BV. - 1361-9209 .- 1879-2340. ; 40, s. 28-42
-
Tidskriftsartikel (refereegranskat)abstract
- We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO2 footprints by 84% when buying standard consumer electronics products.
|
|
| 10. |
- Carling, Kenneth, et al.
(författare)
-
Methodological issues in applying Location Models to Rural areas
- 2010
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases. In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.
|
|
| 11. |
- Carling, Kenneth, et al.
(författare)
-
Testing the gravity p-median model empirically
- 2015
-
Ingår i: Operations Research Perspectives. - : Elsevier. - 2214-7160. ; 2:124
-
Tidskriftsartikel (refereegranskat)abstract
- Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.
|
|
| 12. |
- Carling, Kenneth, et al.
(författare)
-
Var ska sjukhusen ligga?
- 2013
-
Ingår i: Ekonomiska samfundets tidskrift. - 0013-3183 .- 2323-1378. ; :3, s. 165-171
-
Tidskriftsartikel (refereegranskat)abstract
- Denna artikel visar på en metod för att undersöka hur optimal befolkningens fysiska tillgänglighet till sjukvården är. Detta är relevant med tanke på den svenska storregionala omdaningen som säkerligen kommer provocera fram omprövningar av sjukhusens framtida placering.Med Dalarna som exempel fann vi att en ökning från dagens två till tre optimalt lokaliserade sjukhus skulle minska befolkningens genomsnittliga reseavstånd med 25 %.På basis av transportsektorns standardkalkyler för samhällsekonomisk effekter vid resande, samt av kostnader för drift av sjukvård sluter vi dessutom oss till att en komplettering av nuvarande två sjukhus i Dalarna med ett tredje vore samhällsekonomiskt effektivt.
|
|
| 13. |
- Carlucci, S., et al.
(författare)
-
Modeling occupant behavior in buildings
- 2020
-
Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323 .- 1873-684X. ; 174
-
Tidskriftsartikel (refereegranskat)
|
|
| 14. |
|
|
| 15. |
- Gu, Yaxiu, et al.
(författare)
-
Techno-economic analysis of a solar photovoltaic/thermal (PV/T) concentrator for building application in Sweden using Monte Carlo method
- 2018
-
Ingår i: Energy Conversion and Management. - : Elsevier BV. - 0196-8904 .- 1879-2227. ; 165, s. 8-24
-
Tidskriftsartikel (refereegranskat)abstract
- The solar energy share in Sweden will grow up significantly in next a few decades. Such transition offers not only great opportunity but also uncertainties for the emerging solar photovoltaic/thermal (PV/T) technologies. This paper therefore aims to conduct a techno-economic evaluation of a reference solar PV/T concentrator in Sweden for building application. An analytical model is developed based on the combinations of Monte Carlo simulation techniques and multi energy-balance/financial equations, which takes into account of the integrated uncertainties and risks of various variables. In the model, 11 essential input variables, i.e. average daily solar irradiance, electrical/thermal efficiency, prices of electricity/heating, operation & management (OM) cost, PV/T capital cost, debt to equity ratio, interest rate, discount rate, and inflation rate, are considered, while the economic evaluation metrics, such as levelized cost of energy (LCOE), net present value (NPV), and payback period (PP), are primarily assessed. According to the analytical results, the mean values of LCOE, NPV and PP of the reference PV/T connector are observed at 1.27 SEK/kW h (0.127 €/kW h), 18,812.55 SEK (1881.255 €) and 10 years during its 25 years lifespan, given the project size at 10.37 m2 and capital cost at 4482–5378 SEK/m2 (448.2–537.8 €/m2). The positive NPV indicates that the investment on the selected PV/T concentrator will be profitable as the projected earnings exceeds the anticipated costs, depending on the NPV decision rule. The sensitivity analysis and the parametric study illustrate that the economic performance of the reference PV/T concentrator in Sweden is mostly proportional to solar irradiance, debt to equity ratio and heating price, but disproportionate to capital cost and discount rate. Together with additional market analysis of PV/T technologies in Sweden, it is expected that this paper could clarify the economic situation of PV/T technologies in Sweden and provide a useful model for their further investment decisions, in order to achieve sustainable and low-carbon economics, with an expanded quantitative discussion of the real economic or policy scenarios that may lead to those outcomes.
|
|
| 16. |
|
|
| 17. |
- Han, Mengjie, 1985-, et al.
(författare)
-
A novel reinforcement learning method for improving occupant comfort via window opening and closing
- 2020
-
Ingår i: Sustainable cities and society. - : Elsevier BV. - 2210-6707. ; 61
-
Tidskriftsartikel (refereegranskat)abstract
- An occupant's window opening and closing behaviour can significantly influence the level of comfort in the indoor environment. Such behaviour is, however, complex to predict and control conventionally. This paper, therefore, proposes a novel reinforcement learning (RL) method for the advanced control of window opening and closing. The RL control aims at optimising the time point for window opening/closing through observing and learning from the environment. The theory of model-free RL control is developed with the objective of improving occupant comfort, which is applied to historical field measurement data taken from an office building in Beijing. Preliminary testing of RL control is conducted by evaluating the control method’s actions. The results show that the RL control strategy improves thermal and indoor air quality by more than 90 % when compared with the actual historically observed occupant data. This methodology establishes a prototype for optimally controlling window opening and closing behaviour. It can be further extended by including more environmental parameters and more objectives such as energy consumption. The model-free characteristic of RL avoids the disadvantage of implementing inaccurate or complex models for the environment, thereby enabling a great potential in the application of intelligent control for buildings.
|
|
| 18. |
|
|
| 19. |
- Han, Mengjie, et al.
(författare)
-
A review of reinforcement learning methodologies on control systems for building energy
- 2018
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The usage of energy directly leads to a great amount of consumption of the non-renewable fossil resources. Exploiting fossil resources energy can influence both climate and health via ineluctable emissions. Raising awareness, choosing alternative energy and developing energy efficient equipment contributes to reducing the demand for fossil resources energy, but the implementation of them usually takes a long time. Since building energy amounts to around one-third of global energy consumption, and systems in buildings, e.g. HVAC, can be intervened by individual building management, advanced and reliable control techniques for buildings are expected to have a substantial contribution to reducing global energy consumptions. Among those control techniques, the model-free, data-driven reinforcement learning method seems distinctive and applicable. The success of the reinforcement learning method in many artificial intelligence applications has brought us an explicit indication of implementing the method on building energy control. Fruitful algorithms complement each other and guarantee the quality of the optimisation. As a central brain of smart building automation systems, the control technique directly affects the performance of buildings. However, the examination of previous works based on reinforcement learning methodologies are not available and, moreover, how the algorithms can be developed is still vague. Therefore, this paper briefly analyses the empirical applications from the methodology point of view and proposes the future research direction.
|
|
| 20. |
- Han, Mengjie, 1985-, et al.
(författare)
-
An Approach to Data Acquisition for Urban Building Energy Modeling Using a Gaussian Mixture Model and Expectation-Maximization Algorithm
- 2021
-
Ingår i: Buildings. - : MDPI. - 2075-5309. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- In recent years, a building’s energy performance is becoming uncertain because of factors such as climate change, the Covid-19 pandemic, stochastic occupant behavior and inefficient building control systems. Sufficient measurement data is essential to predict and manage a building’s performance levels. Assessing energy performance of buildings at an urban scale requires even larger data samples in order to perform an accurate analysis at an aggregated level. However, data are not only expensive, but it can also be a real challenge for communities to acquire large amounts of real energy data. This is despite the fact that inadequate knowledge of a full population will lead to biased learning and the failure to establish a data pipeline. Thus, this paper proposes a Gaussian mixture model (GMM) with an Expectation-Maximization (EM) algorithm that will produce synthetic building energy data. This method is tested on real datasets. The results show that the parameter estimates from the model are stable and close to the true values. The bivariate model gives better performance in classification accuracy. Synthetic data points generated by the models show a consistent representation of the real data. The approach developed here can be useful for building simulations and optimizations with spatio-temporal mapping.
|
|
| 21. |
- Han, Mengjie, et al.
(författare)
-
Comparison and one-stop shopping after big-box retail entry : a spatial difference-in-difference analysis
- 2018
-
Ingår i: Journal of Retailing and Consumer Services. - : Elsevier BV. - 0969-6989 .- 1873-1384. ; 40, s. 175-187
-
Tidskriftsartikel (refereegranskat)abstract
- This paper empirically measures the potential spillover effects of big-box retail entry on the productivity of incumbent retailers in the entry regions, and investigates whether the effects differ depending on 1) if the entry is in a rural or urban area, and 2) if the incumbent retailers are within retail industries selling substitute or complement goods to those found in IKEA. To identify the IKEA-entry effect, a difference-in-difference model is suitable, but traditionally such estimators neglect the possibility that firms’ sales are determined by a process with spatially interactive responses. If ignored, these responses may cause biased estimates of the IKEA entry effect due to spatial heterogeneity of the treatment effect. One objective of this paper is thus to propose a spatial difference-in-difference estimator accounting for possible spatial spillover effects of IKEA entry. Particular emphasis is placed on the development of a suitable weight matrix accounting for the spatial links between firms, where we allow for local spatial interactions such that the outcome of observed units depends both on their own treatment as well as on the treatment of their neighbors. Our results show that for complementary goods retailers (or one-stop shopping retailers) in Haparanda and Kalmar, productivity increased by 35% and 18%, respectively, due to IKEA entry. No statistically significant effects were found for the entries in Karlstad and Gothenburg, indicating that it is mainly incumbents in smaller entry regions that benefit from IKEA entry. Also, for incumbent retailers selling substitute (or comparison shopping) goods no significant effects were found in any of the entry regions, indicating that it is mainly retailers selling complementary goods that benefit from IKEA entry. Finally, our results also show that ignoring the possibility of spatially correlated treatment effects in the regression models reduces the estimated impact of the IKEA entries in Haparanda and Kalmar on productivity in one-stop shopping retail firms with 3% and 0.1% points, respectively. © 2017 Elsevier Ltd
|
|
| 22. |
- Han, Mengjie, 2013-
(författare)
-
Computational study of the step size parameter of the subgradient optimization method
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.
|
|
| 23. |
- Han, Mengjie, 1985-, et al.
(författare)
-
Generating hourly electricity demand data for large-scale single-family buildings by a decomposition-recombination method
- 2022
-
Ingår i: Energy and Built Environment. - : Elsevier BV. - 2666-1233.
-
Tidskriftsartikel (refereegranskat)abstract
- Household electricity demand has substantial impacts on local grid operation, energy storage and the energy performance of buildings. Hourly demand data at district or urban level helps stakeholders understand the demand patterns from a granular time scale and provides robust evidence in energy management. However, such type of data is often expensive and time-consuming to collect, process and integrate. Decisions built upon smart meter data have to deal with challenges of privacy and security in the whole process. Incomplete data due to confidentiality concerns or system failure can further increase the difficulty of modeling and optimization. In addition, methods using historical data to make predictions can largely vary depending on data quality, local building environment, and dynamic factors. Considering these challenges, this paper proposes a statistical method to generate hourly electricity demand data for large-scale single-family buildings by decomposing time series data and recombining them into synthetics. The proposed method used public data to capture seasonality and the distribution of residuals that fulfill statistical characteristics. A reference building was used to provide empirical parameter settings and validations for the studied buildings. An illustrative case in a city of Sweden using only annual total demand was presented for deploying the proposed method. The results showed that the proposed method can mimic reality well and represent a high level of similarity to the real data. The average monthly error for the best month reached 15.9% and the best one was below 10% among 11 tested months. Less than 0.6% improper synthetic values were found in the studied region.
|
|
| 24. |
- Han, Mengjie, 1985-, et al.
(författare)
-
GRASP and Statistical Bounds for Heuristic Solutions to Combinatorial Problems
- 2019
-
Ingår i: International Journal of Management and Applied Science. - : Institute of Research and Journals (IRAJ). - 2394-7926. ; 5:8, s. 113-119
-
Tidskriftsartikel (refereegranskat)abstract
- The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few heuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds have previously been found reliable when obtained from the Genetic algorithm whereas in this work they have been found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.
|
|
| 25. |
- Han, Mengjie, 1985-
(författare)
-
Heuristic optimization of the p-median problem and population re-distribution
- 2013
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution. The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis. Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling.
|
|
