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.

Sweden experiences heavy snowfall during the winter season and cost effective road maintenance is significantly affected by the routing of snowplows. The routing problem becomes more complex as the SwedishNational Road Administration (Vägverket) sets operational requirements such as satisfying a time window for each road segment. This thesis focuses on route optimization for snowplows after snowfall; to develop and implement an algorithm for finding combinations of generated routes which minimize the total cost. The results are compared to those stated in the licentiate thesis by Doctoral student Nima Golbaharan (2001). The algorithm calculates a lower bound to the problem using a Lagrangian master problem. A common subgradient approach is used to find near-optimal dual variables to be sent to a column-generation program which returns routes for the snowplows. A greedy heuristic chooses a feasible solution, which gives an upper bound to the problem. This entire process is repeated as needed. This method for routing snowplows produces favorable results with a relatively small number of routes and are comparable to Golbaharan's results. An interesting observation involves the allocation of vehicles in which certain depots were regularly over- or under-utilized. This suggests that the quantity and/or distribution of available vehicles may not be optimal.

The issues of global warming and climate change are a worldwide concern and the UK government has committed itself to major reductions in CO2 emissions, the most significant of the six greenhouse gases. Road transport currently accounts for about 22% of total UK emissions of CO2, and has been steadily rising. Therefore, initiatives are required to try and reduce the gas emissions in this sector. The aim of this research has been to develop a computer based vehicle routing model that calculates the overall amount of CO2 emitted from road journeys, as well as time and distance. The model has been used to examine a number of delivery strategies to assess how CO2 emissions vary. The aim has not been to produce new mathematical theories, but to produce an innovative basis for routing which will provide new information and knowledge about how CO2 emissions vary for different minimisation and congestion criteria. The approach used in this research brings together elements from transportation planning and environmental modelling combined with logistics based vehicle routing techniques. The model uses a digitised road network containing predicted traffic volumes, to which speed flow formulae are applied so that a good representation of speed can be generated on each of the roads. This means that the model is uniquely able to address the issue of congestion in the context of freight vehicle routing. It uses driving cycle data to apply variability to the generated speeds to reflect acceleration and deceleration so that fuel consumption, and therefore CO2, can be estimated. Integrated within the model are vehicle routing heuristics to enable routes to be produced which minimise the specified criterion of time, distance or CO2. The results produced by the model show that there is a potential to reduce CO2 emissions by about 5%. However, when other transport externalities are considered overall benefits are dependent on road traffic volumes.

In this thesis, we discussed various possibilities of integrating scheduling decisions with information and constraints from Advanced Process Control (APC) systems in semiconductor Manufacturing. In this context, important questions were opened regarding the benefits of integrating scheduling and APC. An overview on processes, scheduling and Advanced Process Control in semiconductor manufacturing was done, where a description of semiconductor manufacturing processes is given. Two of the proposed problems that result from integrating bith systems were studied and analyzed, they are :Problem of Scheduling with Time Constraints (PTC) and Problem of Scheduling with Equipement health Factor (PEHF). PTC and PEHF have multicriteria objective functions.PTC aims at scheduling job in families on non-identical parallel machines with setup times and time constraints.Non-identical machines mean that not all miachines can (are qualified to) process all types of job families. Time constraints are inspired from APC needs, for which APC control loops must be regularly fed with information from metrology operations (inspection) within a time interval (threshold). The objective is to schedule job families on machines while minimizing the sum of completion times and the losses in machine qualifications.Moreover, PEHF was defined which is an extension of PTC where scheduling takes into account the equipement Health Factors (EHF). EHF is an indicator on the state of a machine. Scheduling is now done by considering a yield resulting from an assignment of a job to a machine and this yield is defined as a function of machine state and job state.

This paper accounts for the work with a website for a company whose real name will not be disclosed in the text of this paper. Instead, they have been assigned the fictitious name Larmbolaget, which can be translated as ‘The Alarm Company’. During our work with Larmbolaget’s website, we consulted a selection of accessibility guidelines from the Web Content Accessibility Guidelines (WCAG) 2.0, developed by a working group within the World Wide Web Consortium, as well as a number of design principles and heuristics outlined in this paper. We also conducted several usability tests on users from our intended target group. All the measures taken were an effort to ensure that Larmbolaget’s website be as accessible and usable as possible. Our conclusion is that the resulting website does comply with the accessibility guidelines and design principles described in this paper, and thus we consider it to be accessible and usable to a wide range of users, including those with disabilities. / Den här rapporten redogör för arbetet med en webbplats åt ett företag vars riktiga namn inte avslöjas i texten i denna rapport. Istället har de tilldeltas det påhittade namnet Larmbolaget. Under arbetet med Larmbolagets webbplats har vi tagit hänsyn till en utvald del av tillgänglighetsriktlinjerna i Web Content Accessibility Guidelines (WCAG) 2.0, utvecklade av en arbetsgrupp inom World Wide Web Consortium, samt ett antal designprinciper och heuristiker som vi sammanfattar i den här rapporten. Vi utförde även ett flertal användartester på användare inom vår tänkta målgrupp. Alla dessa åtgärder var ett försök att göra Larmbolagets webbplats så tillgänglig och användbar som möjligt. Vår slutsats är att den resulterande webbplatsen följer de tillgänglighetsriktlinjer och designprinciper som beskrivs i den här rapporten, och således anser vi den vara tillgänglig och användbar för en stor mängd användare, inklusive dem med funktionshinder.

This research shows optimization approaches to protein folding. The protein folding problem is to predict the compact three dimensional structure of a protein based on its amino acid sequence. This research focuses on ab-initio mathematical models to find provably optimal solutions to the 2D HP-lattice protein folding model. We built two integer programming (IP) models and five constraint programming (CP) models. All the models give provably optimal solutions. We also developed some CP techniques to solve the problem faster and then compared their computational times. We tested the models with several protein instances. My models, while they are probably too slow to use in practice, are significantly faster than the alternatives, and thus are mathematically relevant. We also provided reasons why protein folding is hard using complexity analysis. This research will contribute to showing whether CP can be an alternative to or a complement of IP in the future. Moreover, figuring out techniques combining CP and IP is a prominent research issue and our work will contribute to that literature. It also shows which IP/CP strategies can speed up the running time for this type of problem. Finally, it shows why a mathematical approach to protein folding is especially hard not only mathematically, i.e. NP-hard, but also practically.

Assembly line balancing problem is one of the most studied NP-Hard problems. NP-Hardness leads us to search for a good solution instead of the optimal solution especially for the big-size problems. Meta-heuristic algorithms are the search methods which are developed to find good solutions to the big-size and combinatorial problems. In this study, it is aimed at solving the multi-objective multi-model assembly line balancing problem of a company. A meta-heuristic algorithm is developed to solve the deterministic assembly line balancing problems. The algorithm developed is tested using the test problems in the literature and the the real life problem of the company as well. The results are analyzed and found to be promising and a solution is proposed for the firm.

This study deals with a municipal solid waste management system in which the strategic and tactical decisions are addressed simultaneously. In the system, the number and locations of the transfer facilities which serve to the particular solid waste pick-up points and the landfill are determined. Additionally, routing plans are constructed for the vehicles which collect the solid waste from the pick-up points by regarding the load capacity of the vehicles and shift time restrictions. We formulate this reverse logistics system as a location-routing problem with two facility layers. Mathematical models of the problem are presented, and an iterative capacitated-k-medoids clustering-based heuristic method is proposed for the solution of the problem. Also, a sequential clustering-based heuristic method is presented as a benchmark to the iterative method. Computational studies are performed for both methods on the problem instances including up to 1000 pick-up points, 5 alternative transfer facility sites, and 25 vehicles. The results obtained show that the iterative clustering-based method developed achieves considerable improvement over the sequential clustering-based method.

The emergence of digital technology, social media and ubiquitous computing in the 21stcentury changed customer behavior and created new possibilities, but also challenges, forcompanies offering their services. The new customer generation is more tech-savvy thanever before, and therefore places higher demands on companies to have well-designed experienceswith services that can be consumed through various channels. This study investigatesthese service environments to see if they are actively shaped to cross-channel ecosystemsby the companies or if the companies react to the demands of their customers. Furthermore,the goal of this thesis is to find out how the current theory of cross-channel userexperience can assist in formulating design strategies for service ecosystems. To determinethis, the authors conducted a theoretical analysis of the current IS literature and created,based on that, a cross-channel user experience design framework. Within a case study of aSwedish transportation company, company and user interviews, direct observations of theavailable service artifacts, analysis of documentation, and the design of the user journeyswere executed to assess the as-is ecosystem. On the basis of these results, it was proventhat cross-channel ecosystems are shaped based on user demands. The created frameworkwas applied to formulate a language of critique of the cross-channel user experience designof the underlying case study, and the framework was proven to be applicative to practiceafter adjusting it to its final version.

Amusement parks are a huge business. Guest experiences determine the success or failure for an amusement park. This report suggests an approach to improve guest experience by managing guest flow. The guest happiness optimization problem is formulated into a visitor routing management model. The constraints for this model include attraction attributes and guest behavior. To build the attraction constraints, their information is first gathered from internet, field studies and surveys, and then input into simulation software. Constraints on guest behavior are set up with a literature study and a guest survey. A two phase heuristic is developed to solve this problem with constraints. Candidate routes are generated with a route construction algorithm in the first phase. Visitor distribution and selection on these candidate routes are determined in the second phase using a mixed integer programming solver. Visitor routes are then recommended to the park’s operator side, for them to distribute to guests visiting on their vacations. Data from Disney Epcot are collected and applied in the case study to implement the methodology in this report. Attraction operations capability is maintained at the current level with no additional cost for the project, while guest satisfaction is improved by ensuring the number and type of attractions they visit. In addition, average waiting time for visitors is reduced by at least 70% in the recommended operation strategy. / text