The purpose of this study is to investigate and gain a better understanding of the consumer's point of view of visual sustainability communication with a primary focus on eco-labels on food products. The study will further look into if an environmentally conscious consumer has the ability to make sustainable choices with the guidance of food packaging information. The aim of this study was to answer the question through a questionnaire survey and in further in-depth interviews with comparative visual analysis material of food packaging: Does an environmentally conscious consumer have the ability to make sustainable choices with the support of food packaging information? Based on data collected from the survey and the interviews there are many pitfalls for the consumer when choosing sustainable products because of a number of heuristics that are taken into account. Price and brand still play a big role in purchasing decisions. However, this study showed that there is a desire to act more sustainably. It also showed that there is a need for a new perspective of sustainability and how it is presented on food products. Eco-labels are of great importance, but as for the conclusion: the consumer needs more information to know whether sustainability claims are true or not.

Workforce scheduling is widely used within most industries. A well-outlined and efficient schedule gives cost savings, such as reduced number of overtime hours, increases overall utilization, and facilitates meeting demands. A large and complex schedule, for example, scheduling of a health care workforce, needs to consider many parameters when constructed; it is essential to account for all critical constraints regarding who can dispense a particular medicine, laws restricting the health care system, etcetera. This thesis evaluates two different methods for implementing a workforce scheduling system for one of Linköping’s most well-known restaurants and bars for students, using mixed integer programming and heuristics. Flamman Pub & Disco recruits new employees prior to every semester. Usually, the workforce consists of around 100 employees, and the vast majority of them work either in the bar or in the kitchen. Historically, the scheduling process has been handled manually using Excel. This does, however, take up much time for the operations manager, something considered frowned upon. Therefore, this thesis suggests an automated scheme for future scheduling processes. Because Flamman is a student organization, they do not hold the capital to invest in expensive licensed optimization software. However, literature studies have shown that heuristics such as large neighborhood search can generate sufficient performance, and therefore the investigation of free-of-charge software using a heuristic approach is conducted. The constructed framework uses a mixed integer programming model, which also lays the cornerstone for the two heuristics: a reverse constructive heuristic and a large neighborhood search. The results retrieved from the analysis prove that a heuristic can be a helpful tool for upcoming recruitment periods. There are, however, recommended areas for improvement regarding the current state of the heuristic.

For larger instances of multi-objective optimisation problems, the exact Pareto frontier can be both difficult and time-consuming to calculate. There is a wide range of methods to find feasible solutions to such problems, but techniques for finding good optimistic bounds to compare the feasible solutions with are missing. In this study, we investigate the use of Lagrangian relaxation to create optimistic bounds to bi-objective optimisation problems with complicating side constraints. The aim is to develop an effective method to produce optimistic bounds that are closer to the Pareto frontier than the commonly used linear programming bounds.  In order to use Lagrangian relaxation on the bi-objective problem, the objectives are combined using the weighted sum method. A Lagrangian dual function is then constructed by relaxing the complicating constraints and the subgradient method is used to optimise the dual problem in order to find an optimistic solution. By solving the single-objective problem for multiple weights, an optimistic bound to the Pareto frontier can be constructed. The subgradient method also includes a heuristic to find feasible solutions. The feasible solutions found by the heuristic form a pessimistic bound to the frontier. The method has been implemented and tested on several instances of a capacitated facility location problem with cost and CO2 emission as objectives. The results indicate that, by using Lagrangian relaxation, an optimistic bound close to the Pareto frontier can be found in a relatively short time. The heuristic used also manages to produce good pessimistic bounds, and hence the Pareto frontier can be tightly enclosed. The optimistic bounds found by Lagrangian relaxation are better and more consistent along the Pareto frontier than the bounds found by linear programming.

<p>As stressed by the Society for Industrial and Applied Mathematics (SIAM): Applied mathematics, in partnership with computational science, is essential in solving many real-world problems. Combinatorial optimization focuses on problems arising from discrete structures such as graphs and polyhedra. This thesis deals with extremal graphs and strings and focuses on two problems: the Erdos' problem on multiplicities of complete subgraphs and the maximum number of distinct squares in a string.<br />The first part of the thesis deals with strengthening the bounds for the minimum proportion of monochromatic t cliques and t cocliques for all 2-colourings of the edges of the complete graph on n vertices. Denote by k_t(G) the number of cliques of order t in a graph G. Let k_t(n) = min{k_t(G)+k_t(\overline{G})} where \overline{G} denotes the complement of G of order n. Let c_t(n) = {k_t(n)} / {\tbinom{n}{t}} and c_t be the limit of c_t(n) for n going to infinity. A 1962 conjecture of Erdos stating that c_t = 2^{1-\tbinom{t}{2}} was disproved by Thomason in 1989 for all t > 3. Tighter counterexamples have been constructed by Jagger, Stovicek and Thomason in 1996, by Thomason for t < 7 in 1997, and by Franek for t=6 in 2002. We present a computational framework to investigate tighter upper bounds for small t yielding the following improved upper bounds for t=6,7 and 8: c_6 \leq 0.7445 \times 2^{1- \tbinom{6}{2}}, c_7\leq 0.6869\times 2^{1- \tbinom{7}{2}}, and c_8 \leq 0.7002\times 2^{1- \tbinom{8}{2}}. The constructions are based on a large but highly regular variant of Cayley graphs for which the number of cliques and cocliques can be expressed in closed form. Considering the quantity e_t=2^{\tbinom{t}{2}-1} c_t, the new upper bound of 0.687 for e_7 is the first bound for any e_t smaller than the lower bound of 0.695 for e_4 due to Giraud in 1979.<br />The second part of the thesis deals with extremal periodicities in strings: we consider the problem of the maximum number of distinct squares in a string. The importance of considering as key variables both the length n and the size d of the alphabet is stressed. Let (d,n)-string denote a string of length n with exactly d distinct symbols. We investigate the function \sigma_d(n) = max {s(x) | x} where s(x) denotes the number of distinct primitively rooted squares in a (d,n)-string x. We discuss a computational framework for computing \sigma_d(n) based on the notion of density and exploiting the tightness of the available lower bound. The obtained computational results substantiate the hypothesized upper bound of n-d for \sigma_d(n). The structural similarities with the approach used for investigating the Hirsch bound for the diameter of a polytope of dimension d having n facets is underlined. For example, the role played by (d,2d)-polytope was presented in 1967 by Klee and Walkup who showed the equivalency between the Hirsch conjecture and the d-step conjecture.</p> / Doctor of Philosophy (PhD)

The purpose of this study was to determine if the use of primary source historical documents used in conjunction with the heuristics associated with historical reasoning (sourcing, corroboration, and contextualization) would lead to a subsequent development of historical empathy. Three intact groups (already formed history classes) from Northeast High School in Philadelphia, Pennsylvania were studied throughout a baseline and four trials for this study. One group was designated as the experimental condition and received primary source historical documents as well as scaffolding of the historical reasoning heuristics of sourcing, corroboration, and contextualization. The next group was designated as the comparison condition which received the primary source historical documents but no scaffolding on the aforementioned heuristics. The final group was designated as the control condition and received traditional textbook instruction throughout the four main trials of the study. Results showed that mean scores of the heuristics involved in historical reasoning as well as historical empathy increased simultaneously for the experimental as well as the comparison group throughout the study, with the experimental group showing the highest mean gains. However, whether training in the historical reasoning heuristics of sourcing, corroboration, and contextualization lead to historical empathy cannot be conclusively proven from this current study. / Educational Psychology

A study was conducted to determine the preferences for the design of distributed meeting rooms used for video enhanced electronic meeting systems (VEMS). Although there is a significant body of literature in the group communication domain, the research in this multidisciplinary area has paid minimal attention to users' environmental preferences in the design of a meeting space. A basic science approach through three studies was used to explore the variables that defined the design of a distributed meeting space from the user's perspective. Twenty-five inexperienced college-enrolled participants and twenty-five experienced Naval professionals used foam-core pieces to create a design of their ideal distributed meeting space. Thirty-seven variables were used to categorize qualitative attributes of the designs. Three types of designs emerged from the sample population: v-shaped, conference (u-shaped or oval), and theater (auditorium) style. A nonexperimental design was used to measure the impact of the heuristics on the users' physical design of their distributed meeting spaces. Post-meeting evaluation results were promising and indicated that the heuristics were usable and that participating in the design could have a positive impact on user's subjective rating of their meeting experience. Overall, inexperienced users did not believe that the heuristics were necessary to determine the best room design for their team's needs. In the third study, six experts conducted an expert evaluation of a distributed meeting room site. Most experts were not able to identify context-specific design issues such as camera angle and lighting with the static information that they were provided. The experts subjective ratings indicated that the heuristics were usable and were useful for room designers. The overall findings indicated that experience level had a significant impact on user's perception of important equipment in a distributed meeting room. Naïve users were more concerned with visual communication and assigned more importance to public displays (p=.035). Experienced users were more concerned with audio communication and assigned more importance to microphone control (p=.024). In addition, general findings from this research include a new methodology for generating participatory ergonomic tools. / Ph. D.

Generalized hill climbing (GHC) algorithms provide a unifying framework for describing several discrete optimization problem local search heuristics, including simulated annealing and tabu search. A necessary and a sufficient convergence condition for GHC algorithms are presented. The convergence conditions presented in this dissertation are based upon a new iteration classification scheme for GHC algorithms. The convergence theory for particular formulations of GHC algorithms is presented and the implications discussed. Examples are provided to illustrate the relationship between the new convergence conditions and previously existing convergence conditions in the literature. The contributions of the necessary and the sufficient convergence conditions for GHC algorithms are discussed and future research endeavors are suggested. / Ph. D.

Identifying a globally optimal solution for an intractable discrete optimization problem is often cost prohibitive. Therefore, solutions that are within a predetermined threshold are often acceptable in practice. This dissertation introduces the concept of B-acceptable solutions where B is a predetermined threshold for the objective function value. It is difficult to assess a priori the effectiveness of local search algorithms, which makes the process of choosing parameters to improve their performance difficult. This dissertation introduces the B-acceptable solution probability in terms of B-acceptable solutions as a finite-time performance measure for local search algorithms. The B-acceptable solution probability reflects how effectively an algorithm has performed to date and how effectively an algorithm can be expected to perform in the future. The B-acceptable solution probability is also used to obtain necessary asymptotic convergence (with probability one) conditions. Upper and lower bounds for the B-acceptable solution probability are presented. These expressions assume particularly simple forms when applied to specific local search strategies such as Monte Carlo search and threshold accepting. Moreover, these expressions provide guidelines on how to manage the execution of local search algorithm runs. Computational experiments are reported to estimate the probability of reaching a B-acceptable solution for a fixed number of iterations. Logistic regression is applied as a tool to estimate the probability of reaching a B-acceptable solution for values of B close to the objective function value of a globally optimal solution as well as to estimate this objective function value. Computational experiments are reported with logistic regression for pure local search, simulated annealing and threshold accepting applied to instances of the TSP with known optimal solutions. / Ph. D.

Generalized hill climbing (GHC) algorithms are introduced, as a tool to address difficult discrete optimization problems. Particular formulations of GHC algorithms include simulated annealing (SA), local search, and threshold accepting (T A), among. others. A proof of convergence of GHC algorithms is presented, that relaxes the sufficient conditions for the most general proof of convergence for stochastic search algorithms in the literature (Anily and Federgruen [1987]). Proofs of convergence for SA are based on the concept that deteriorating (hill climbing) transitions between neighboring solutions are accepted by comparing a deterministic function of both the solution change cost and a temperature parameter to a uniform (0,1) random variable. GHC algorithms represent a more general model, whereby deteriorating moves are accepted according to a general random variable. Computational results are reported that illustrate relationships that exist between the GHC algorithm's finite-time performance on three problems, and the general random variable formulations used. The dissertation concludes with suggestions for further research. / Ph. D.

No