Negotiation-Based Capacity Planning With A Learning Mechanism Using Adaptive Neurofuzzy Inference System

In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performances. This study focuses on the development of an integrated framework to allocate limited budget in a multiple-factory environment. We develop a negotiation framework with learning mechanism to allocate autonomously finite budget provided by a headquarter and to facilitate the use of limited manufacturing resources that are scattered over individual factories. The outcome of the experiments shows good prediction of the opponent offers during negotiation, so it enables the reduction of negotiation time

Development of Complementary Fresh-Food Systems Through the Exploration and Identification of Profit-Maximizing, Supply Chains

abstract: One of the greatest 21st century challenges is meeting the needs of a growing world population expected to increase 35% by 2050 given projected trends in diets, consumption and income. This in turn requires a 70-100% improvement on current production capability, even as the world is undergoing systemic climate pattern changes. This growth not only translates to higher demand for staple products, such as rice, wheat, and beans, but also creates demand for high-value products such as fresh fruits and vegetables (FVs), fueled by better economic conditions and a more health conscious consumer. In this case, it would seem that these trends would present opportunities for the economic development of environmentally well-suited regions to produce high-value products. Interestingly, many regions with production potential still exhibit a considerable gap between their current and ‘true’ maximum capability, especially in places where poverty is more common. Paradoxically, often high-value, horticultural products could be produced in these regions, if relatively small capital investments are made and proper marketing and distribution channels are created. The hypothesis is that small farmers within local agricultural systems are well positioned to take advantage of existing sustainable and profitable opportunities, specifically in high-value agricultural production. Unearthing these opportunities can entice investments in small farming development and help them enter the horticultural industry, thus expand the volume, variety and/or quality of products available for global consumption. In this dissertation, the objective is three-fold: (1) to demonstrate the hidden production potential that exist within local agricultural communities, (2) highlight the importance of supply chain modeling tools in the strategic design of local agricultural systems, and (3) demonstrate the application of optimization and machine learning techniques to strategize the implementation of protective agricultural technologies. As part of this dissertation, a yield approximation method is developed and integrated with a mixed-integer program to estimate a region’s potential to produce non-perennial, vegetable items. This integration offers practical approximations that help decision-makers identify technologies needed to protect agricultural production, alter harvesting patterns to better match market behavior, and provide an analytical framework through which external investment entities can assess different production options.Dissertation/ThesisDoctoral Dissertation Industrial Engineering 201

A methodology for the strategic staff planning in public universities

The number of public universities worldwide has been increased substantially in the last decades. In Europe, such growth has been accompanied of several regulatory changes in regard of different aspects such as: the Bologna process, the European Credit Transfer System (ECTS), new mechanisms for resource management, growing interests in patents and entrepreneurship and the increasing emphasis on university-industry relationship, among others. Accordingly, universities should adopt new management strategies; otherwise, they would face problems around weak financing, personnel management (from both academics and administration departments) and treatment of talent, amongst others. The strategic staff planning consists in determining the long term quantity and type of required resources according to a set of restrictions (e.g. personnel, academic and economic policies). The lack of a strategic planning, could be translated into an increment in personnel costs, an inadequate determination of workforce size to the actual university needs, and an inadequate workforce composition in regard of various aspects such as: the generational renewal, experience, expertise in diverse knowledge fields and an adequate balance between teaching and research profiles. The determination of a methodology, which includes the mathematical modeling by means of a Mixed Integer Linear Program, for the strategic planning of public universities, is the main object of the present thesis. The optimization of the strategic planning addresses various aspects such as: i) policies on personnel hiring, firing and promotion; ii) workforce heterogeneity (set of categories); iii) and the adoption of an optimization criterion, in this case based not only on economics, but also on other aspects such as the required service level and the achievement of a workforce composition according to a preferable one. The optimization model, and the corresponding analyses in regard of diverse study cases on different personnel, academic and economic policies, are the main contributions of the present thesis. The contents of the thesis are divided into 7 principal chapters. Chapter 2 offers a state of the art on knowledge intensive organizations (KIOs) and the strategic capacity planning, also particularizing for the case of universities. Next, Chapter 3 identifies the most relevant characteristics of KIOs in general, and of universities in particular. This chapter gives rise to the development of a methodology for the determination of the strategic staff planning, which is stated in Chapter 4. This methodology consists of different phases, each one treated in the following chapters: the characterization of the problem (Chapter 5), the mathematical formulation of the optimization model for the strategic planning (Chapter 6) and the evaluation of the optimization model in different study cases (Chapter 7). Finally, the conclusions of the previously mentioned analyses and the potentiality of the proposed tools are summarized in Chapter 8. The main conclusions of the thesis indicate, among others, that the proposed optimization model successes in obtaining a close composition to a preferable one taking into account constraints associated to budget and required service level, as well as others affecting personnel (hiring, firing and promotions) and academic policies. In this sense, the model contributes to decision making processes on strategic staff planning, thus facilitating the sustainable development of public universitiesEl nombre d'universitats públiques ha crescut considerablement en les últimes dècades en el món. A nivell europeu, aquest creixement s'ha vist acompanyat de nombrosos canvis de regulació en l'àmbit de l'ensenyament com el procés de Bolònia, les reformes de l'Espai Europeu d'Investigació (ECTS), nous mecanismes de gestió de recursos, interès en les patents i l'emprenedoria, i el creixent èmfasi en les relacions universitat/empresa, entre d'altres. Amb tot això les universitats que no adoptin noves estratègies de planificació o no considerin aquests canvis, s'enfrontaran a problemes tals com finançament debilitat, i relacionats amb la gestió de personal (tant docent com administratiu) i el tractament del talent, entre d'altres. La planificació estratègica de personal consisteix en determinar a llarg termini la quantitat i tipologia dels recursos de personal d'acord a un conjunt de criteris (polítiques de personal, acadèmiques i econòmiques). La falta d'un pla estratègic es podria traduir en un increment del cost de personal, una inadequació del volum del mateix a les necessitats reals de la universitat, i una composició poc adequada en referència, per exemple, al relleu generacional, experiència, capacitats en diversos àmbits de coneixement, balanç entre perfils docents i investigadors. La determinació d'una metodologia, que inclou la formulació i resolució d'un model matemàtic d'optimització, pel pla estratègic per al cas de les universitats públiques és l'objecte principal d'aquesta tesi. L'optimització del pla estratègic té en compte diversos aspectes tals com: i) polítiques referents a la contractació, acomiadament i promoció de personal; ii) l'heterogeneïtat dels treballadors (conjunt de categories); iii) i l'adopció d'un criteri d'optimització, en aquest cas basat no només en mètriques econòmiques, sinó també d'acord amb altres aspectes tals com el nivell de servei requerit i la consecució d'una composició de la plantilla de treballadors d'acord a un ideal. Aquesta eina d'optimització, així com les anàlisis al voltant de diversos casos d'estudi avaluant diferents polítiques de personal, acadèmiques i econòmiques, són les contribucions principals d'aquesta tesi. Els continguts de la tesi es divideixen en 7 capítols principals. El Capítol 2 ofereix un estat de l'art sobre les organitzacions intensives en coneixement (KIOs en anglès), i la planificació estratègica de la capacitat, particularitzant en el cas de les universitats. Complementàriament, el Capítol 3 identifica les característiques rellevants de les KIOs en general, i de les universitats en particular. Aquest capítol dona peu al desenvolupament d'una metodologia per a la determinació del pla estratègic de personal, tractat al Capítol 4. Aquesta metodologia consta de diferents fases, cadascuna de les quals tractada en els següents capítols: la caracterització del problema (Capítol 5), la formulació matemàtica d'un model d'optimització per al pla estratègic (Capítol 6) i l'avaluació d'aquesta eina d'optimització d'acord a diferents casos d'estudi (Capítol 7). Finalment, les conclusions d'aquestes anàlisis s'ofereixen al Capítol 8. Les conclusions principals de la tesi indiquen, entre d'altres, que el model d'optimització proposat determina satisfactòriament una composició de la plantilla de personal a llarg termini i d'acord a un ideal, considerant diversos aspectes o restriccions relacionades amb el pressupost, nivell de servei requerit i d'altres afectant polítiques de personal (contractacions, acomiadaments i promocions) i acadèmiques. En aquest sentit, el model s'esdevé com una eina que pot contribuir a la presa de decisions al voltant del pla estratègic --a llarg termini-- de personal, facilitant el desenvolupament sostenible de les universitats públiques