Matching Items (10)
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- All Subjects: Sustainability
- All Subjects: Optimization
Description
Brundtland’s definition of sustainability is the ability to “meet the needs of the present<br/>without compromising the ability of future generations to meet their needs” (IISD, 2021). But<br/>what if there are no future generations? Social sustainability, the sector of sustainability that<br/>foregrounds the well-being and livelihoods of people (and thereby continuation of humanity), is<br/>included in definitions within the sustainability field, but less developed in sustainability<br/>practice. In an effort to bridge this gap of knowledge, 14 U.S. cities and over 100 sustainability<br/>policies were analyzed for their social sustainability performance. An eight-item analytical<br/>framework that deals with differing areas of social equity guided the analysis. Results found that<br/>most cities’ sustainability departments fell short of truly addressing social sustainability<br/>concerns. Out of the eight items, the most frequently addressed were housing security and racial<br/>and gender equality whereas few, if any, cities addressed the more specific social concerns of<br/>immigration, technology and media, or arts/cultural preservation. Future research is<br/>recommended to gain a better understanding of the ways existing cities can improve in this area.
ContributorsWeekes, Daniel Buckner (Co-author) / Tam, Joey (Co-author) / Brian, Jennifer (Thesis director) / Keeler, Lauren Withycombe (Thesis director) / N/A, N/A (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Lithium ion batteries are quintessential components of modern life. They are used to power smart devices — phones, tablets, laptops, and are rapidly becoming major elements in the automotive industry. Demand projections for lithium are skyrocketing with production struggling to keep up pace. This drive is due mostly to the rapid adoption of electric vehicles; sales of electric vehicles in 2020 are more than double what they were only a year prior. With such staggering growth it is important to understand how lithium is sourced and what that means for the environment. Will production even be capable of meeting the demand as more industries make use of this valuable element? How will the environmental impact of lithium affect growth? This thesis attempts to answer these questions as the world looks to a decade of rapid growth for lithium ion batteries.
ContributorsMelton, John (Author) / Brian, Jennifer (Thesis director) / Karwat, Darshawn (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Every year, more than 11 million maritime containers and 11 million commercial trucks arrive to the United States, carrying all types of imported goods. As it would be costly to inspect every container, only a fraction of them are inspected before being allowed to proceed into the United States. This dissertation proposes a decision support system that aims to allocate the scarce inspection resources at a land POE (L-POE), to minimize the different costs associated with the inspection process, including those associated with delaying the entry of legitimate imports. Given the ubiquity of sensors in all aspects of the supply chain, it is necessary to have automated decision systems that incorporate the information provided by these sensors and other possible channels into the inspection planning process. The inspection planning system proposed in this dissertation decomposes the inspection effort allocation process into two phases: Primary and detailed inspection planning. The former helps decide what to inspect, and the latter how to conduct the inspections. A multi-objective optimization (MOO) model is developed for primary inspection planning. This model tries to balance the costs of conducting inspections, direct and expected, and the waiting time of the trucks. The resulting model is exploited in two different ways: One is to construct a complete or a partial efficient frontier for the MOO model with diversity of Pareto-optimal solutions maximized; the other is to evaluate a given inspection plan and provide possible suggestions for improvement. The methodologies are described in detail and case studies provided. The case studies show that this MOO based primary planning model can effectively pick out the non-conforming trucks to inspect, while balancing the costs and waiting time.
ContributorsXue, Liangjie (Author) / Villalobos, Jesus René (Thesis advisor) / Gel, Esma (Committee member) / Runger, George C. (Committee member) / Maltz, Arnold (Committee member) / Arizona State University (Publisher)
Created2012
Description
The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs and regulatory requirements set by entities such as unions and FAA. With the magnitude of operation of the prominent players in the airline industry today, the crew staffing problem proves very large and has become heavily reliant on operations research solution methodologies. An area of opportunity that has not yet been extensively researched lies in the planning of crew vacation. This paper develops a model driven by the idea of system risk that constructs an optimal vacation grid for the time period of one year. The model generates a daily allocation that maximizes vacation offering while ensuring a given level of system reliability. The model is then implemented using data from US Airways and model improvements are provided for practical application in the airline industry based on the output.
ContributorsFisher, Tignes Noel (Author) / Gel, Esma (Thesis director) / Jacobs, Tim (Committee member) / Clough, Michael (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
Description
Brundtland’s definition of sustainability is the ability to “meet the needs of the present without compromising the ability of future generations to meet their needs” (IISD, 2021). But what if there are no future generations? Social sustainability, the sector of sustainability that foregrounds the well-being and livelihoods of people (and thereby continuation of humanity), is included in definitions within the sustainability field, but less developed in sustainability practice. In an effort to bridge this gap of knowledge, 14 U.S. cities and over 100 sustainability policies were analyzed for their social sustainability performance. An eight-item analytical framework that deals with differing areas of social equity guided the analysis. Results found that most cities’ sustainability departments fell short of truly addressing social sustainability concerns. Out of the eight items, the most frequently addressed were housing security and racial and gender equality whereas few, if any, cities addressed the more specific social concerns of immigration, technology and media, or arts/cultural preservation. Future research is recommended to gain a better understanding of the ways existing cities can improve in this area.
ContributorsTam, Joey (Co-author) / Weekes, Daniel (Co-author) / Brian, Jennifer (Thesis director) / Keeler, Lauren (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Every year, millions of guests visit theme parks internationally. Within that massive population, accidents and emergencies are bound to occur. Choosing the correct location for emergency responders inside of the park could mean the difference between life and death. In an effort to provide the utmost safety for the guests of a park, it is important to make the best decision when selecting the location for emergency response crews. A theme park is different from a regular residential or commercial area because the crowds and shows block certain routes, and they change throughout the day. We propose an optimization model that selects staging locations for emergency medical responders in a theme park to maximize the number of responses that can occur within a pre-specified time. The staging areas are selected from a candidate set of restricted access locations where the responders can store their equipment. Our solution approach considers all routes to access any park location, including areas that are unavailable to a regular guest. Theme parks are a highly dynamic environment. Because special events occurring in the park at certain hours (e.g., parades) might impact the responders' travel times, our model's decisions also include the time dimension in the location and re-location of the responders. Our solution provides the optimal location of the responders for each time partition, including backup responders. When an optimal solution is found, the model is also designed to consider alternate optimal solutions that provide a more balanced workload for the crews.
ContributorsLivingston, Noah Russell (Author) / Sefair, Jorge (Thesis director) / Askin, Ronald (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Corporate social responsibility (CSR) is a fascinating and complex topic. There is consensus that companies both make a large impact on the world and have a responsibility beyond profits. The challenge with this responsibility is that determining businesses' responsibility and measuring the impact remains unclear. Scholars most often point to the early to mid 1900s as its starting point and the increased economic growth and workers' unions occurring in the 1950s as one of the reasons for scholars paying more attention to the topic. This thesis project analyzes current examples of CSR from Starbucks and IBM. These companies have reputations for their positive CSR practices. Both companies' availability of information, the vast number of their CSR practices, and efforts to measure the impact set them apart. IBM and Starbucks stand out because of the sheer volume of CSR activities they have, and when examined closely, the mixed, primarily good, impact of these activities is revealed. Having a high number of CSR practices alone does not equate to doing CSR well. Instead, companies' CSR should be examined based on both the number of practices and their impact. Considering both of these metrics will help consumers, as well as other stakeholders, better evaluate the success or failure of CSR in a business.
ContributorsSullivan, Victoria Mary (Author) / Brian, Jennifer (Thesis director) / York, Abigail (Committee member) / School of Human Evolution and Social Change (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Breeding seeds to include desirable traits (increased yield, drought/temperature resistance, etc.) is a growing and important method of establishing food security. However, besides breeder intuition, few decision-making tools exist that can provide the breeders with credible evidence to make decisions on which seeds to progress to further stages of development. This thesis attempts to create a chance-constrained knapsack optimization model, which the breeder can use to make better decisions about seed progression and help reduce the levels of risk in their selections. The model’s objective is to select seed varieties out of a larger pool of varieties and maximize the average yield of the “knapsack” based on meeting some risk criteria. Two models are created for different cases. First is the risk reduction model which seeks to reduce the risk of getting a bad yield but still maximize the total yield. The second model considers the possibility of adverse environmental effects and seeks to mitigate the negative effects it could have on the total yield. In practice, breeders can use these models to better quantify uncertainty in selecting seed varieties
ContributorsOzcan, Ozkan Meric (Author) / Armbruster, Dieter (Thesis advisor) / Gel, Esma (Thesis advisor) / Sefair, Jorge (Committee member) / Arizona State University (Publisher)
Created2019
Description
Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of the vehicles have a range that is less than those powered by gasoline. These factors together create a "range anxiety" in drivers, which causes the drivers to worry about the utility of alternative-fuel and electric vehicles and makes them less likely to purchase these vehicles. For the new vehicle technologies to thrive it is critical that range anxiety is minimized and performance is increased as much as possible through proper routing and scheduling. In the case of long distance trips taken by individual vehicles, the routes must be chosen such that the vehicles take the shortest routes while not running out of fuel on the trip. When many vehicles are to be routed during the day, if the refueling stations have limited capacity then care must be taken to avoid having too many vehicles arrive at the stations at any time. If the vehicles that will need to be routed in the future are unknown then this problem is stochastic. For fleets of vehicles serving scheduled operations, switching to alternative-fuels requires ensuring the schedules do not cause the vehicles to run out of fuel. This is especially problematic since the locations where the vehicles may refuel are limited due to the technology being new. This dissertation covers three related optimization problems: routing a single electric or alternative-fuel vehicle on a long distance trip, routing many electric vehicles in a network where the stations have limited capacity and the arrivals into the system are stochastic, and scheduling fleets of electric or alternative-fuel vehicles with limited locations to refuel. Different algorithms are proposed to solve each of the three problems, of which some are exact and some are heuristic. The algorithms are tested on both random data and data relating to the State of Arizona.
ContributorsAdler, Jonathan D (Author) / Mirchandani, Pitu B. (Thesis advisor) / Askin, Ronald (Committee member) / Gel, Esma (Committee member) / Xue, Guoliang (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2014
Description
Transformational sustainability science demands that stakeholders and researchers consider the needs and values of future generations in pursuit of solutions to sustainability problems. This dissertation research focuses on the real-world problem of unsustainable water governance in the Phoenix region of Central Arizona. A sustainability transition is the local water system is necessary to overcome sustainability challenges and scenarios can be used to explore plausible and desirable futures to inform a transition, but this requires some methodological refinements. This dissertation refines scenario methodology to generate water governance scenarios for metropolitan Phoenix that: (i) feature enhanced stakeholder participation; (ii) incorporate normative values and preferences; (iii) focus on governance actors and their activities; and (iv) meet an expanded set of quality criteria. The first study in the dissertation analyzes and evaluates participatory climate change scenarios to provide recommendations for the construction and use of scenarios that advance climate adaptation and mitigation efforts. The second study proposes and tests a set of plausibility indications to substantiate or evaluate claims that scenarios and future projections could become reality, helping to establish the legitimacy of radically different or transformative scenarios among an extended peer community. The case study of water governance begins with the third study, which includes a current state analysis and sustainability appraisal of the Phoenix-area water system. This is followed by a fourth study which surveys Phoenix-area water decision-makers to better understand water-related preferences for use in scenario construction. The fifth and final study applies a multi-method approach to construct future scenarios of water governance in metropolitan Phoenix in 2030 using stakeholder preferences, among other normative frames, and testing systemic impacts with WaterSim 5.0, a dynamic simulation model of water in the region. The scenarios are boundary objects around which stakeholders can weigh tradeoffs, set priorities and reflect on impacts of water-related activities, broadening policy dialogues around water governance in central Arizona. Together the five studies advance transformational sustainability research by refining methods to engage stakeholders in crafting futures that define how individuals and institutions should operate in transformed and sustainable systems.
ContributorsKeeler, Lauren Withycombe (Author) / Wiek, Arnim (Thesis advisor) / White, Dave D (Committee member) / Lang, Daniel J (Committee member) / Arizona State University (Publisher)
Created2014