Stampede October 15, 2019

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Dynamic Facility Location with Modular Capacities : Models, Algorithms and Applications in Forestry

Les décisions de localisation sont souvent soumises à des aspects dynamiques comme des changements dans la demande des clients. Pour y répondre, la solution consiste à considérer une flexibilité accrue concernant l’emplacement et la capacité des installations. Même lorsque la demande est prévisible, trouver le planning optimal pour le déploiement et l'ajustement dynamique des capacités reste un défi. Dans cette thèse, nous nous concentrons sur des problèmes de localisation avec périodes multiples, et permettant l'ajustement dynamique des capacités, en particulier ceux avec des structures de coûts complexes. Nous étudions ces problèmes sous différents points de vue de recherche opérationnelle, en présentant et en comparant plusieurs modèles de programmation linéaire en nombres entiers (PLNE), l'évaluation de leur utilisation dans la pratique et en développant des algorithmes de résolution efficaces. Cette thèse est divisée en quatre parties. Tout d’abord, nous présentons le contexte industriel à l’origine de nos travaux: une compagnie forestière qui a besoin de localiser des campements pour accueillir les travailleurs forestiers. Nous présentons un modèle PLNE permettant la construction de nouveaux campements, l’extension, le déplacement et la fermeture temporaire partielle des campements existants. Ce modèle utilise des contraintes de capacité particulières, ainsi qu’une structure de coût à économie d’échelle sur plusieurs niveaux. L'utilité du modèle est évaluée par deux études de cas. La deuxième partie introduit le problème dynamique de localisation avec des capacités modulaires généralisées. Le modèle généralise plusieurs problèmes dynamiques de localisation et fournit de meilleures bornes de la relaxation linéaire que leurs formulations spécialisées. Le modèle peut résoudre des problèmes de localisation où les coûts pour les changements de capacité sont définis pour toutes les paires de niveaux de capacité, comme c'est le cas dans le problème industriel mentionnée ci-dessus. Il est appliqué à trois cas particuliers: l'expansion et la réduction des capacités, la fermeture temporaire des installations, et la combinaison des deux. Nous démontrons des relations de dominance entre notre formulation et les modèles existants pour les cas particuliers. Des expériences de calcul sur un grand nombre d’instances générées aléatoirement jusqu’à 100 installations et 1000 clients, montrent que notre modèle peut obtenir des solutions optimales plus rapidement que les formulations spécialisées existantes. Compte tenu de la complexité des modèles précédents pour les grandes instances, la troisième partie de la thèse propose des heuristiques lagrangiennes. Basées sur les méthodes du sous-gradient et des faisceaux, elles trouvent des solutions de bonne qualité même pour les instances de grande taille comportant jusqu’à 250 installations et 1000 clients. Nous améliorons ensuite la qualité de la solution obtenue en résolvent un modèle PLNE restreint qui tire parti des informations recueillies lors de la résolution du dual lagrangien. Les résultats des calculs montrent que les heuristiques donnent rapidement des solutions de bonne qualité, même pour les instances où les solveurs génériques ne trouvent pas de solutions réalisables. Finalement, nous adaptons les heuristiques précédentes pour résoudre le problème industriel. Deux relaxations différentes sont proposées et comparées. Des extensions des concepts précédents sont présentées afin d'assurer une résolution fiable en un temps raisonnable.Location decisions are frequently subject to dynamic aspects such as changes in customer demand. Often, flexibility regarding the geographic location of facilities, as well as their capacities, is the only solution to such issues. Even when demand can be forecast, finding the optimal schedule for the deployment and dynamic adjustment of capacities remains a challenge. In this thesis, we focus on multi-period facility location problems that allow for dynamic capacity adjustment, in particular those with complex cost structures. We investigate such problems from different Operations Research perspectives, presenting and comparing several mixed-integer programming (MIP) models, assessing their use in practice and developing efficient solution algorithms. The thesis is divided into four parts. We first motivate our research by an industrial application, in which a logging company needs to locate camps to host the workers involved in forestry operations. We present a MIP model that allows for the construction of additional camps, the expansion and relocation of existing ones, as well as partial closing and reopening of facilities. The model uses particular capacity constraints that involve integer rounding on the left hand side. Economies of scale are considered on several levels of the cost structure. The usefulness of the model is assessed by two case studies. The second part introduces the Dynamic Facility Location Problem with Generalized Modular Capacities (DFLPG). The model generalizes existing formulations for several dynamic facility location problems and provides stronger linear programming relaxations than the specialized formulations. The model can address facility location problems where the costs for capacity changes are defined for all pairs of capacity levels, as it is the case in the previously introduced industrial problem. It is applied to three special cases: capacity expansion and reduction, temporary facility closing and reopening, and the combination of both. We prove dominance relationships between our formulation and existing models for the special cases. Computational experiments on a large set of randomly generated instances with up to 100 facility locations and 1000 customers show that our model can obtain optimal solutions in shorter computing times than the existing specialized formulations. Given the complexity of such models for large instances, the third part of the thesis proposes efficient Lagrangian heuristics. Based on subgradient and bundle methods, good quality solutions are found even for large-scale instances with up to 250 facility locations and 1000 customers. To improve the final solution quality, a restricted model is solved based on the information collected through the solution of the Lagrangian dual. Computational results show that the Lagrangian based heuristics provide highly reliable results, producing good quality solutions in short computing times even for instances where generic solvers do not find feasible solutions. Finally, we adapt the Lagrangian heuristics to solve the industrial application. Two different relaxations are proposed and compared. Extensions of the previous concepts are presented to ensure a reliable solution of the problem, providing high quality solutions in reasonable computing times

Permanent Housing for Seasonal Workers? A Generalized Peak Load Investment Model for Farm Worker Housing

Many seasonal workers are housed in transitory accommodations, including tents and vehicles. In this study, we analyze the supply side of this problem by assuming that a public agent must house the workers through direct public investment. A peak load model is adapted to develop investment rules for the least-cost provision of seasonal worker housing, adding an interacting multi-season component to existing models. Based on this model and the data from three prototype projects, the majority of the least-cost investment would be in permanent, but seasonally occupied, housing.farmworker housing, investment rules, peak load model, public housing, seasonal labor, Farm Management, Labor and Human Capital, Public Economics, R31, H75, J43, G31,

A case study exploring the effects of using an integrative STEM curriculum on eighth grade students’ performance and engagement in the mathematics classroom

To address the need to improve student achievement in STEM disciplines, effort has been made to develop a new of tools for STEM education (Bybee, 2013). The Robotics and Engineering Design Curriculum (REDC) provides students an opportunity to develop systems thinking abilities while integrating science and mathematics concepts. Using an exploratory case study approach within a situated cognition framework, this study examines the effects of using REDC on 54 eighth grade students’ performance and engagement during 5-week integrative STEM instruction in the mathematics and science class. Situational factors that contribute to students’ success in learning STEM concepts are also examined. This study employed mixed-methods techniques. The quantitative data collected included pre/post achievement tests and pre/post motivation and engagement scale (MES) surveys. Quantitative data analysis included reliability analyses and paired sample t-tests. The results of the reliability analyses for the achievement test and MES survey report acceptable Cronbach’s alpha (.843 and .787, respectively). Qualitative data collected included semi-structured interviews, field notes and student artifacts (engineering notebook and printed prototypes). Qualitative data analysis used coding procedures suggested by Saldana (2012) where patterns were identified and grouped to allow the emergence of themes. Collectively, the data was triangulated to support six emerging themes. The emerging themes regarding the effect of using the curriculum are as follows: (1) the developing anthropomorphic relationship with the robot enhances engagement, (2) engagement is impacted by purposeful and intentional physical action, and (3) purposeful collaboration promotes engagement through the construction of meaning and interaction. Three themes emerged identifying factors that contribute to success: (1) learning environment must have transformative learning potential, (2) learning experiences underpinned by design thinking contribute to success and (3) contextual relevance is enhanced when students have the freedom to their design learning journey. This study addresses the need for research into the implementation of 3-D design and manufacturing in the middle school classroom. Bybee, R. W. (2013). The case for STEM education: Challenges and opportunities. National Science Teachers Association. Saldaña, J. (2012). The coding manual for qualitative researchers (No. 14). Los Angeles, Ca: Sage

Simulating activities: Relating motives, deliberation, and attentive coordination

Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied “off-task” activities (e.g., waiting), non-intellectual motives (e.g., hunger), sustaining a goal state (e.g., playful interaction), and coupled perceptual-motor dynamics (e.g., following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly, activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that “working” is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human-robot systems

Expert Systems for Environmental Screening. An Application in the Lower Mekong Basin

This research report describes MEXSES, a rule-based expert system for environmental impact assessment at a screening level, implemented for the analysis of water resources development projects in the Lower Mekong Basin. The report makes a brief review of environmental impact assessment methods and tools. It discusses expert systems technology, with emphasis on environmental applications. The Lower Mekong Basin and its specific environmental problems, as well as the Mekong Secretariat's environmental policy are examined. Subsequently, the software system is described from a user's perspective, followed by a detailed description of the methodology employed and its implementation. In the final chapter, a number of issues around the successful application of such a system are discussed, including a number of suggested improvements and extensions to the current operational prototype