I investigated the presence, utility, and emergence of tacit knowledge in 9 study participants who used assistive-augmentative technology. I conducted phenomenologic interviews, audio-taping, and transcribed the interview with the written consent of the participants. Sixteen highly trained experts critiqued the final product of the interviews and answered a 25-question survey instrument. Non-parametric statistical processes were chosen to conduct inferential hypotheses testing. Wilcoxon - Mann Whitney U tests and Kruskal - Wallis One-Way ANOVA (alpha level of 0.05) were used for questions 1-10, and a 2 x R (R = 3 or 4) contingency table and Fisher's Exact Chi-Square were used for questions 11- 25. The responses to survey questions showed no statistically significant differences or interaction for the variables gender, expertise, and service (p < 0.0017). Qualitative analysis found discernable heuristics and ideation that was indicative of the presence of implicitly learned tacit knowledge in study participants; the utility of tacit knowledge emerged during direct observation or when participant's engaged in analogy, storytelling, and metaphor. The participants in this study used introspeculation, a learning style framed by reflection and introspection on the validity of one's own knowledge and the value of what is learned from life experience and in the classroom. The introspeculative examined the presence and utility of tacit knowledge in decision-making, and questioned the veracity of sources and resources that guide them on the path of life. The study suggested that tacit knowledge not only informs the practice of therapists and technology users but may assist classroom teachers facing student involvement in individual education plans (IEPs), Individuals with Disabilities Education Act (IDEA), or section 504 of the Americans with Disabilities Act (ADA).

Electric cars are projected to become the vehicles of the future. A major barrier for their expansion is range anxiety stemming from the limited range a typical EV can travel. EV batteries' performance and capacity are affected by many factors. In particular, the decrease in ambient temperature below a certain threshold will adversely affect the battery's efficiency. This research develops deterministic and two-stage stochastic program model for charging stations' optimal location to facilitate the routing decisions of delivery services that use EVs while considering the variability inherent in climate and customer demand. To evaluate the proposed formulation and solution approach's performance, Fargo city in North Dakota is selected as a tested. For the first chapter, we formulated this problem as a mixed-integer linear programming model that captures the realistic charging behavior of the DCFC's in association with the ambient temperature and their subsequent impact on the EV charging station location and routing decisions. Two innovative heuristics are proposed to solve this challenging model in a realistic test setting, namely, the two-phase Tabu Search-modified Clarke and Wright algorithm and the Sweep-based Iterative Greedy Adaptive Large Neighborhood algorithm. The results clearly indicate that the EV DCFC charging station location decisions are highly sensitive to the ambient temperature, the charging time, and the initial state-of-charge. The results provide numerous managerial insights for decision-makers to efficiently design and manage the DCFC EV logistic network for cities that suffer from high-temperature fluctuations. For the second chapter, a novel solution approach based on the progressive hedging algorithm is presented to solve the resulting mathematical model and to provide high-quality solutions within reasonable running times for problems with many scenarios. We observe that the location-routing decisions are susceptible to the EV logistic's underlying climate, signifying that decision-makers of the DCFC EV logistic network for cities that suffer from high-temperature fluctuations would not overlook the effect of climate to design and manage the respective logistic network efficiently.

Mathematical proof is an important topic in mathematics education research. Many researchers have addressed various aspects of proof. One aspect that has not been addressed is what common traits are shared by those who are successful at creating proof. This research investigates the common traits in the thought processes of undergraduate students who are considered successful by their professors at creating mathematical proof. A successful proof is defined as a proof that successfully accomplishes at least one of DeVilliers (2003) six roles of proof and demonstrates adequate mathematical content, knowledge, deduction and logical reasoning abilities. This will typically be present in a proof that fits Weber's (2004) semantic proof category, though some syntactic proofs may also qualify. Proof creation can be considered a type of problem, and Schoenfeld's (1985) categories of resources, heuristics, control and ability are used as a framework for reporting the results. The research involved a) finding volunteers based on professorial recommendations; b) administering a proof questionnaire and conducting a video recorded interview about the results; and then c) holding a second video recorded interview where new proofs were introduced to the subjects during the interviews. The researcher used Goldin's (2000) recommendations for making task based research scientific and made interview protocols in the style of Galbraith (1981). The interviews were transcribed and analyzed using Strauss and Corbin's (1990) methods. The resulting codes corresponded with Schoenfeld's four categories, so his category names were used. Resources involved the mathematical content knowledge available to the subject. Heuristics involved strategies and techniques used by the subject in creating the proof. Control involved choices in implementing resources and heuristics, planning and using time wisely. Beliefs involved the subjects' beliefs about mathematics, proof, and their own skills. These categories are seen in other research involving proof but not all put together. The research has implications for further research possibilities in how the categories all work together and develop in successful proof creators. It also has implications for what should be taught in proofs courses to help students become successful provers.

Property developers and investors seek to understand the drivers of prices for office and retail space. Through literature, we learn that size and age, locational attributes, physical features of the properties, and economic variables are significant determinants of commercial property prices. However, previous work has narrowly focused on aspects akin to formal structures and ignored the role of institutions, especially conventions and social norms incredibly, and what influences the behaviour of the property developers and investors while making the pricing decision. Therefore, the goal of this study was to understand how prices for commercial properties are determined in Uganda. The objectives of the study were to understand the role of conventions and social norms found in the property market environment on price determination and to explore the behaviour tendencies/heuristics exhibited by the players during the pricing decision-making process. The study was qualitative in nature. The researcher interviewed property owners, developers, institutional investors, and key informants to understand the conventions and social norms that exist in the property market and how they ultimately influence the pricing decision of commercial buildings. This study reveals that conventions exist in the Ugandan property markets. The conventions signal a price to the players in the property environment. However, due to information asymmetry and irrationality, each player interprets the price signals differently, using heuristics to develop the final price. This study helps researchers understand the role of individual behaviour/heuristics in advancing our understanding of institutions and the effects of the two on commercial property pricing, the economy at large and its consequences on economic policy.

The scheduling of a tennis school’s operation at a general tennis club is today done manually. This is a time consuming task, usually taking 2-4 weeks for the person responsible. This thesis aims to mathematically formulate the tennis school scheduling problem (TSSP), and to develop a computer based solution procedure to automate the scheduling process. The mathematical formulation of the problem has the structure of an optimization problem and the solution procedure that is developed is a heuristic algorithm for the specific purpose of this problem. Furthermore, a heuristic local search algorithm to improve the initial solution is developed, and the model is then tested on real data in a case study at a padel club in Stockholm. Furthermore, the result from the solution procedure is compared with the manually created schedule by the club on some key parameters from the mathematical model. The computerized solution procedure outperformed the manual scheduling procedure in terms of execution time and most of the times in the objective value of the generated schedule. In terms of the mathematical formulation neither the manually created schedule nor the schedules created by the algorithm gives feasible solutions to the problem. However, the padel club deems the schedules usable and will continue with the ongoing process to implement the model. / Schemaläggning av en tennisskolas verksamhet hanteras vanligtvis av en eller flera ansvariga från tennisklubben och utförs manuellt. Det är en tidskrävande uppgift som kräver uppföljning och återkoppling med alla deltagare, vilket kan ta flera veckor. Den här masteruppsatsen ämnar att matematiskt formulera tennisskolans schemaläggningsproblem, "tennis school scheduling problem" (TSSP), och utveckla en schemaläggningsalgoritm för att heuristiskt lösa TSSP som kan imple-menteras med objektorienterad programmering för att automatisera schemaläggningen. Utöver det är en lokal sökalgoritm framtagen för att förbättra schemat skapat av schemaläggningsalgo-ritmen. Algoritmerna är testade på en padelklubbs träningsverksamhet för att jämföra resultaten från algoritmerna mot deras manuellt framtagna schema. Den automatiserade schemaläggningsal-goritmen är e˙ektivare än att manuellt schemalägga verksamheten gällande tidsåtgång och även ofta i målvärde definierat i matematiska modellen. Baserat på data från padelklubben och så som problemet är uppställt i samråd med dem, möter varken det manuellt framtagna schemat eller det genererat med schemaläggningsalgoritmen, efter förbättringsalgoritmen tillämpats, de krav som är ställda på schemat. Trots det är det genererade schemat brukbart enligt padelklubben och de kommer arbeta med att implementera automatiseringen av schemaläggningen.Den automatiserade processen för att ta fram ett schema är tänkt att användas som ett verk-tyg för en schemaansvarig person. Det kan användas för att generera förslag på scheman baserat på deltagares tillgängligheter, för att bespara personens administrativa arbete med schemaläggnin-gen. Mindre ändringar kan sen göras i ett genererat schema och det är enligt dem själva en stor besparing i arbete jämfört med hur det går till i dagsläget.

The aim of this thesis is to make use of real world travel time and demand data and implement an algorithm which designs bus networks. Consideration is taken to both passenger and bus operator interests. Thereafter answering the questions: How well does the algorithm perform when applied to Södertälje, Sweden? Can the proposed method assist in the network design stage of real bus network planning? Heuristics and the multiobjective genetic algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm II) were chosen. Three different problem cases were set up. It was found that the high computation time poses a great obstacle, over 80 hours for a network of 58 stations and 18 routes. Even then a longer run time would have led to improved results. When comparing a smaller problem, 24 stations and four routes, to the real bus routes it is based on, a superior solution was found based on the model. It is however not possible to argue for the proposed network being superior to the existing one if replaced in reality due to the fact a subsystem is modelled. It is believed that the proposed algorithm may be of assistance to traffic planners in the way of suggesting single links or routes, not replacing the complete bus network design process. / Målet med denna studie är att använda verklig resedata och efterfrågan och implementera en algoritm som designar busslinjenät med avseende på passagerar -och operatörsintressen. Därefter svara på frågorna: Hur bra presterar algoritmen när den tillämpas på Södertälje, Sverige? Kan den föreslagna algoritmen bidra i designfasen av ett verkligt busslinjenät? Heuristik och den multiobjektiva genetiska algoritmen NSGA-II (Non-dominated Sorting Genetic Algorithm II) användes. Tre olika problem ställdes upp. Det framkom att den långa beräkningstiden är ett stort hinder, över 80 timmar för ett busslinjenät med 58 stationer och 18 busslinjer. Den begränsande faktorn var den långa körtiden, bättre lösningar hade kunnat hittas om programmet fått fortsätta köra. Endast ett mindre nätverk, 24 stationer med fyra busslinjer, baserades på verkliga busslinjer och kunde jämföras. Det resulterade i lösningar som var bättre än de verkliga busslinjerna inom ramen för modellen. Det kan dock inte betraktas som bättre än det verkliga nätverket i mån av att ersätta det, då endast ett subsystem modellerades. Det anses att den föreslagna algoritmen kan vara av assistans för trafikplanerare genom att föreslå länkar mellan busstationer eller hela busslinjer, däremot inte ersätta den nuvarande processen av att designa bussnätverk.

This thesis aims to study the use of Critical System Heuristic (CSH) in the requirements engineering (RE) process of a student software project. We have studied a software project within the framework of the TDDD96 course at Linköping University. The project consisted of a group of computer science students working with a representative from a company. As part of the course, the students had done the sustainability exercise SusAF, in which they evaluated their project based on multiple sustainability metrics. We have conducted one round of interviews with the RE student, the company representative, and an expert in the area. The answers were encoded and mapped to 12 CSH questions before being presented in the Ideal map table. The results produced by CSH show the many benefits of integrating CSH into the course. We have proposed different ways of integrating CSH with the SusAF exercise. From the result, we realized the importance of consulting a third party that could provide an outside perspective on different issues. However, an essential aspect of using CSH is to consult the appropriate party. To this end, we found that CSH could be used internally to point in the right direction.

Again for the past couple of years, e-business has become a hot topic. This same act of reselling items through the internet is known as e-businesses. Many e-business sites aim to build customer loyalty. Various aspects influence the performance of e-business websites, particularly usability or the simplicity by which users may use the website, which has been proven to become a key component in online company success. Maybe this research uses a survey assessment based on Nielsen's usability heuristics to analyze the usability of Myntra and Ajio e-business websites.This also evaluates whether e-business websites, such as Myntra and Ajio, provide more useful features for accomplishing usability procedures in much less time and with ease.

Scheduling large real world problems is a complex process and finding high quality solutions is not a trivial task. In cooperation with Trimble MRM Ltd., who provide scheduling solutions for many large companies, a problem is identified and modelled. It is a general model which encapsulates several important scheduling, routing and resource allocation problems in literature. Many of the state-of-the-art heuristics for solve scheduling problems and indeed other problems require specialised heuristics tailored for the problem they are to solve. While these provide good solutions a lot of expert time is needed to study the problem, and implement solutions. This research investigates methods to enhance existing search based methods. We study hyperheuristic techniques as a general search based heuristic. Hyperheuristics raise the generality of the solution method by using a set of tools (low level heuristics) to work on the solution. These tools are problem specific and usually make small changes to the problem. It is the task of the hyperheuristic to determine which tool to use and when. Low level heuristics using exact/heuristic hybrid method are used in this thesis along with a new Tabu based hyperheuristic which decreases the amount of CPU time required to produce good quality solutions. We also develop and investigate the Variable Fitness Function approach, which provides a new way of enhancing most search-based heuristics in terms of solution quality. If a fitness function is pushing hard in a certain direction, a heuristic may ultimately fail because it cannot escape local minima. The Variable Fitness Function allows the fitness function to change over the search and use objective measures not used in the fitness calculation. The Variable Fitness Function and its ability to generalise are extensively tested in this thesis. The two aims of the thesis are achieved and the methods are analysed in depth. General conclusions and areas of future work are also identified.

This thesis aims to review and analyze the scheduling problem in general and Job Shop Scheduling Problem (JSSP) in particular and the solution techniques applied to these problems. The JSSP is the most general and popular hard combinational optimization problem in manufacturing systems. For the past sixty years, an enormous amount of research has been carried out to solve these problems. The literature review showed the inherent shortcomings of solutions to scheduling problems. This has directed researchers to develop hybrid approaches, as no single technique for scheduling has yet been successful in providing optimal solutions to these difficult problems, with much potential for improvements in the existing techniques. The hybrid approach complements and compensates for the limitations of each individual solution technique for better performance and improves results in solving both static and dynamic production scheduling environments. Over the past years, hybrid approaches have generally outperformed simple Genetic Algorithms (GAs). Therefore, two novel priority heuristic rules are developed: Index Based Heuristic and Hybrid Heuristic. These rules are applied to benchmark JSSP and compared with popular traditional rules. The results show that these new heuristic rules have outperformed the traditional heuristic rules over a wide range of benchmark JSSPs. Furthermore, a hybrid GA is developed as an alternate scheduling approach. The hybrid GA uses the novel heuristic rules in its key steps. The hybrid GA is applied to benchmark JSSPs. The hybrid GA is also tested on benchmark flow shop scheduling problems and industrial case studies. The hybrid GA successfully found solutions to JSSPs and is not problem dependent. The hybrid GA performance across the case studies has proved that the developed scheduling model can be applied to any real-world scheduling problem for achieving optimal or near-optimal solutions. This shows the effectiveness of the hybrid GA in real-world scheduling problems. In conclusion, all the research objectives are achieved. Finaly, the future work for the developed heuristic rules and the hybrid GA are discussed and recommendations are made on the basis of the results. / Board of Trustees, Endowment Fund Project, KPK University of Engineering and Technology (UET), Peshawar and Higher Education Commission (HEC), Pakistan