This dissertation studies models for locating facilities in time varying demand environments. We describe the characteristics of the time varying demand that motivate the analysis of our location models in terms of total demand and the change in value and location of the demand of each customer. The first part of the dissertation is devoted to the dynamic location model, which determines the optimal time and location for establishing capacitated facilities when demand and cost parameters are time varying. This model minimizes the total cost over a discrete and finite time horizon for establishing, operating, and closing facilities, including the transportation costs for shipping demand from facilities to customers. The model is solved using Lagrangian relaxation and Benders? decomposition. Computational results from different time varying total demand structures demonstrate, empirically, the performance of these solution methods. The second part of the dissertation studies two location models where relocation of facilities is not allowed and the objective is to determine the optimal location of capacitated facilities that will have a good performance when demand and cost parameters are time varying. The first model minimizes the total cost for opening and operating facilities and the associated transportation costs when demand and cost parameters are time varying. The model is solved using Benders? decomposition. We show that in the presence of high relocation costs of facilities (opening and closing costs), this model can be solved as a special case by the dynamic location model. The second model minimizes the maximum regret or opportunity loss between a robust configuration of facilities and the optimal configuration for each time period. We implement local search and simulated annealing metaheuristics to efficiently obtain near optimal solutions for this model.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed.

In mobile computing systems, predicting the next location of a mobile wireless user has gained interest over the past decade. Location prediction may have a wide-range of application areas such as network load balancing, advertising and web page prefetching. In the literature, there exist many location predictors which are divided into two main classes: domain-independent and domain-specific. Song et al. compare the prediction accuracy of the domain-independent predictors from four major families, namely, Markov-based, compression-based, PPM and SPM predictors on Dartmouth&#039 / s campus-wide Wi-Fi mobility data. As a result, the low-order Markov predictors are found as the best predictor. In another work, Bayir et al. propose a domain-specific location predictor (LPMP) as the application of a framework used for discovering mobile cell phone user profiles. In this thesis, we evaluate LPMP and the best Markov predictor with Dartmouth&#039 / s campus-wide Wi-Fi mobility data in terms of accuracy. We also propose a simple method which improves the accuracy of LPMP slightly in the location prediction part of LPMP. Our results show that the accuracy of the best Markov predictor is better than that of LPMP in total. However, interestingly, LPMP yields more accurate results than the best Markov predictor does for the users with the low prediction accuracy.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.

Bibliotek och liknande arkiv har funnits i hundratals år och är en viktig del av ett lands kulturella arbete. De fungerar även som en mötesplats för alla; oavsett ålder, social eller ekonomisk bakgrund. Dessvärre visar färska rapporter att antalet utlåningar och besök minskar på biblioteken. Kulturförvaltningen i Stockholms Stad arbetar för närvarande med att ta fram en Strukturplan gällande biblioteken i staden för en kommande fyraårs period. Syftet med planen är att rekognosera hur läget ser ut idag för att sedan sätta upp mål för hur verksamheten ska utvecklas. För att ge stöd till framtagningen av strukturplanen kommer denna studie utvärdera hur väl lokaliseringsmodellen location-allocation är lämpad som beslutsunderlag för placering av bibliotek samt vilken inverkan olika typer av behovspunkter har på resultatet. Genom att applicera modellen i fallstudien Stockholms Stads bibliotek, kan modellen utvärderas för att se om den kan användas vid liknade frågeställningar i framtiden. Med hjälp av data över var folk bor, arbetar och rör sig utvärderas modellen i två steg. Först kommer varje behovstyp att analyseras var för sig och därefter testas tre metoder för att slå ihop de olika typerna för att skapa en mer enhetlig bild. Resultaten visar att modellen location-allocation har stor potential för att användas som beslutsstöd för bibliotekens verksamhet. Utifrån de olika behovspunkterna kan strategiska placeringar hittas och en bredare bild ges av var folk bor, arbetar och hur de rör sig. Varje enskilt resultat berättar mer om var människorna i staden befinner sig och det är också lätt att se skillnader på till exempel var folk bor och arbetar, samt var man bör finnas för att nå ut till den yngre befolkningen jämfört med befolkningen i sin helhet. De tre metoderna för att sammanslagning av resultaten visade sig alla vara effektiva och pålitliga. Att visa alla delresultat på en och samma karta, förslagsvis med hjälp av en interaktiv PDF, ger en tydlig bild över de olika behovstypernas betydelse och inverkan. Kluster av valda platser kan hittas och ringas in. De två andra metoderna, MCE-analys och linjarisering, ger en bra bild över vilka strategiska placeringar som finns, båda kan vara användbara för att på ett snabbt och enkelt sätt förmedla resultatet. En del begränsningar och osäkerheter finns dock med modellen som är viktiga att beakta. Lösningsalgoritmen sker heuristiskt vilket gör att det kan vara svårt att förstå exakt hur den räknar och vilken inverkan olika parametrar har. Därför är det viktigt att en omfattande genomgång görs för den verksamhet som ska undersökas, det vill säga, vilka behov finns, hur de ser på sin verksamhet och vilka parametrar tror de inverkar på besökarnas rörelsemönster. Slutligen ska det betonas att Kulturförvaltningen, som har varit en del av denna studie och som har gett sin input till analysen, har ansett att modellen och materialet är användbart. Då avsikten med analysen inte var att hitta exakta placeringar av bibliotek utan snarare att få en översiktlig bild av var de bör placeras för att bäst nå ut till kommunens invånare kan slutsatsen dras att resultaten från location-allocation modellen ger en värdefull input som beslutsunderlag. Det är dock viktigt att ha i åtanke att resultatet från modellen inte visar en exakt verklighet, utan att den endast ger ett förslag på hur man bäst når ut till befolkningen. Det ska också tilläggas att detta bara är en del av många när det kommer till biblioteksplanering. Till exempel spelar bibliotekens lånestatistik, utbud och inriktning en viktig roll när det kommer till att utvärdera verksamheten. / Libraries and similar archives have existed for hundreds of years and are an important part of a country's cultural work. It also serves as meeting place for all, regardless of age, social and economic background. However, recent studies state that the physical loaning of literature and the number of visitors at libraries are decreasing. Kulturförvaltningen (The Department of Art and Culture), a part of the municipality of Stockholm, is currently producing a structure plan for the development of the libraries in the coming four years. The purpose of the plan is to evaluate the current circumstances and thereafter set targets on how their business should develop. To support the work with the structure plan this study will evaluate the model location-allocation and examine if it is suitable as a decision basis for locating libraries and what impact different types of demand points have on the result. By applying the model in a case study, consisting of the libraries in Stockholm, the model can be evaluated in terms of usefulness in similar problems in the future. With the help of data of where people live, work and how they move, the model will be evaluated in two stages. In the first stage, different demand points will be examined separately and thereafter three methods will be tested to combine the different types to create a more uniform picture. The results show that the location-allocation model has a large potential to be used as a decision basis for library planning. With the help of different demand points, strategic locations can be found and a wider picture is given of where people live, work and how they move. Each individual result tells more about where the citizens are and it is also easy to see distinctions between the different types of demand, for example where people live and work and where the libraries should be located to reach the younger population in comparison to the population as a whole. The three methods for merging the results all ended up to be both effective and trustworthy. To show all the sub-results in the same map, preferably with the help of an interactive PDF, highlights the importance and impact different demands have as well as allowing patterns or clusters to be found and marked. The two other methods tested, a MCE-analysis and linearization, are both useful to show strategic locations and to quickly and simply communicate results. However, there are some limitations and uncertainties with the model that are important to take into consideration. The algorithm used to solve the problem is heuristic, making it hard to understand exactly how it calculates and what impact different parameters have. Consequently, it is important to make an extensive review of the business that will be examined, more specific, what are their demands, how do they look at their business and what parameters do they believe impact the movement pattern of visitors. Finally, it should be emphasized that Kulturförvaltningen has been a part of this study from the beginning and they have given their support and input into the analysis throughout the process. In the end, they considered the model and the results from it to be useful in the decision-making process. It is important to keep in mind that the results of the model do not show an exact reality, the intention of the analysis was to develop an overview of where libraries should be approximately located, rather than to find exact locations. The end result being libraries located to better reach their citizens. However, the above is only looking at one part of many when it comes to library site planning and many other issues such as the libraries lending rate, supply and overall focus play an important role when it comes to evaluating their business.

Digitized by Kansas State University Libraries

Call number: LD2668 .T4 1961 S63

Call number: LD2668 .T4 1978 L49 / Master of Arts

One of the trickiest challenges introduced by cellular communications networks is mobility prediction for Location Based-Services (LBSs). Hence, an accurate and efficient mobility prediction technique is particularly needed for these networks. The mobility prediction technique incurs overheads on the transmission process. These overheads affect properties of the cellular communications network such as delay, denial of services, manual filtering and bandwidth. The main goal of this research is to enhance a mobility prediction scheme in cellular communications networks through three phases. Firstly, current mobility prediction techniques will be investigated. Secondly, innovation and examination of new mobility prediction techniques will be based on three hypothesises that are suitable for cellular communications network and mobile user (MU) resources with low computation cost and high prediction success rate without using MU resources in the prediction process. Thirdly, a new mobility prediction scheme will be generated that is based on different levels of mobility prediction. In this thesis, a new mobility prediction scheme for LBSs is proposed. It could be considered as a combination of the cell and routing area (RA) prediction levels. For cell level prediction, most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the New Markov-Based Mobility Prediction (NMMP) and Prediction Location Model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression and insufficient accuracy. In this thesis, Location Prediction based on a Sector Snapshot (LPSS) is introduced, which is based on a Novel Cell Splitting Algorithm (NCPA). This algorithm is implemented in a micro cell in parallel with the new prediction technique. The LPSS technique, compared with two classic prediction techniques and the experimental results, shows the effectiveness and robustness of the new splitting algorithm and prediction technique. In the cell side, the proposed approach reduces the complexity cost and prevents the cell level prediction technique from performing in time slots that are too close. For these reasons, the RA avoids cell-side problems. This research discusses a New Routing Area Displacement Prediction for Location-Based Services (NRADP) which is based on developed Ant Colony Optimization (ACO). The NRADP, compared with Mobility Prediction based on an Ant System (MPAS) and the experimental results, shows the effectiveness, higher prediction rate, reduced search stagnation ratio, and reduced computation cost of the new prediction technique.