Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Project scheduling and cost minimization with multiple availability constrained resources under stochastic conditions

The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.

Equivalence of piecewise-linear approximation and Lagrangian relaxation for network revenue management

The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

Diversified query expansion

La diversification des résultats de recherche (DRR) vise à sélectionner divers documents à partir des résultats de recherche afin de couvrir autant d’intentions que possible. Dans les approches existantes, on suppose que les résultats initiaux sont suffisamment diversifiés et couvrent bien les aspects de la requête. Or, on observe souvent que les résultats initiaux n’arrivent pas à couvrir certains aspects. Dans cette thèse, nous proposons une nouvelle approche de DRR qui consiste à diversifier l’expansion de requête (DER) afin d’avoir une meilleure couverture des aspects. Les termes d’expansion sont sélectionnés à partir d’une ou de plusieurs ressource(s) suivant le principe de pertinence marginale maximale. Dans notre première contribution, nous proposons une méthode pour DER au niveau des termes où la similarité entre les termes est mesurée superficiellement à l’aide des ressources. Quand plusieurs ressources sont utilisées pour DER, elles ont été uniformément combinées dans la littérature, ce qui permet d’ignorer la contribution individuelle de chaque ressource par rapport à la requête. Dans la seconde contribution de cette thèse, nous proposons une nouvelle méthode de pondération de ressources selon la requête. Notre méthode utilise un ensemble de caractéristiques qui sont intégrées à un modèle de régression linéaire, et génère à partir de chaque ressource un nombre de termes d’expansion proportionnellement au poids de cette ressource. Les méthodes proposées pour DER se concentrent sur l’élimination de la redondance entre les termes d’expansion sans se soucier si les termes sélectionnés couvrent effectivement les différents aspects de la requête. Pour pallier à cet inconvénient, nous introduisons dans la troisième contribution de cette thèse une nouvelle méthode pour DER au niveau des aspects. Notre méthode est entraînée de façon supervisée selon le principe que les termes reliés doivent correspondre au même aspect. Cette méthode permet de sélectionner des termes d’expansion à un niveau sémantique latent afin de couvrir autant que possible différents aspects de la requête. De plus, cette méthode autorise l’intégration de plusieurs ressources afin de suggérer des termes d’expansion, et supporte l’intégration de plusieurs contraintes telles que la contrainte de dispersion. Nous évaluons nos méthodes à l’aide des données de ClueWeb09B et de trois collections de requêtes de TRECWeb track et montrons l’utilité de nos approches par rapport aux méthodes existantes.

Características del diseño de una relación estratégica comunitaria y marketing en emprendimiento en el sector de ambientadores y cosméticos

En nuestro país el sector de ambientadores y cosméticos ha presentado un crecimiento económico constante y notable, proyectando a Colombia para el año 2032 como un dirigente en la elaboración de cosméticos y productos de aseo. La biodiversidad colombiana ofrece múltiples recursos, incluyendo una gran diversidad de aromas naturales, es un importante mercado para producción de cosméticos sin la utilización de productos artificiales. El presente trabajo de investigación tiene por objetivo determinar las características del diseño de una relación estratégica comunitaria y marketing en la creación de una empresa de cosméticos y ambientadores. Ésta investigación se realiza bajo la recopilación de información del sector y principalmente de la organización, dentro de un estudio empírico-analítico descriptivo. Estableciendo resultados que finalmente dan respuesta a la utilidad de estrategias comunitarias en la actualidad. En el caso de estudio de la nueva empresa "Jolie Le Petit" en un sector en crecimiento, ofrece múltiples oportunidades de negocio y permite generar ideas innovadoras para la venta de productos. La facilidad de cambio y la inclusión en la comunidad posibilita el acercamiento a los clientes, asegurando la permanencia en el mercado indicado. Considerando la posibilidad que la inversión extranjera en el sector pueda afectar notablemente el mercado nacional. Mediante el análisis concluimos que la estrategia de mercadeo comunitaria es adecuada y aplicable a este tipo de empresa. "Jolie Le Petit" además de ser una unidad es también un actor social, estando inmersa en una comunidad en donde juega un papel vital el ser percibida como un buen vecino, ofreciendo a los clientes confianza compromiso y relación continua.

Evidence of higher photosynthetic plasticity in the early successional Guazuma ulmifolia Lam. compared to the late successional Hymenaea courbaril L. grown in contrasting light environments

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Contribuições da conectância de rede e complexidade da dinâmica do sistema de trocas gasosas para a estabilidade na utilização de luz por espécies florestais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

A multi-resource load balancing algorithm for cloud cache systems

With the advent of cloud computing model, distributed caches have become the cornerstone for building scalable applications. Popular systems like Facebook [1] or Twitter use Memcached [5], a highly scalable distributed object cache, to speed up applications by avoiding database accesses. Distributed object caches assign objects to cache instances based on a hashing function, and objects are not moved from a cache instance to another unless more instances are added to the cache and objects are redistributed. This may lead to situations where some cache instances are overloaded when some of the objects they store are frequently accessed, while other cache instances are less frequently used. In this paper we propose a multi-resource load balancing algorithm for distributed cache systems. The algorithm aims at balancing both CPU and Memory resources among cache instances by redistributing stored data. Considering the possible conflict of balancing multiple resources at the same time, we give CPU and Memory resources weighted priorities based on the runtime load distributions. A scarcer resource is given a higher weight than a less scarce resource when load balancing. The system imbalance degree is evaluated based on monitoring information, and the utility load of a node, a unit for resource consumption. Besides, since continuous rebalance of the system may affect the QoS of applications utilizing the cache system, our data selection policy ensures that each data migration minimizes the system imbalance degree and hence, the total reconfiguration cost can be minimized. An extensive simulation is conducted to compare our policy with other policies. Our policy shows a significant improvement in time efficiency and decrease in reconfiguration cost.

Comparison of Wildlife Impacts Associated with Uranium In-Situ Recovery and Wind Farms in Wyoming

Wyoming has multiple resources including non-renewable sources, renewable sources, as well as its wildlife. Two of these resources are uranium and wind. Currently wind farms in Wyoming are generating approximately 5 million MW of power, with less of an impact on wildlife than in-situ facilities. In-situ facilities in 2007 produced an estimated 32 million MW of power from uranium, with a greater impact to wildlife than wind farms. Both resources have a great potential in Wyoming and both will have an impact on wildlife. Currently wind farms show less of an impact on wildlife but they are also producing fewer megawatts. The potential for wind-generated energy over the next century shows wildlife impacts will be greater than impacts from ISR facilities.

The effects of participation in an Internet -based project on the development of global knowledge, global mindedness, and global pedagogy among preservice social studies teachers

In order to prepare younger generations to live in a world characterized by interconnectedness, developing global and international perspectives for future teachers has been recommended by the National Council for the Social Studies and the National Council for the Accreditation of Teacher Education. The purpose of this study was to investigate the effects that participation in the International Communication and Negotiation Simulation (ICONS), an Internet-based communication project has on preservice social studies teachers' global knowledge, global mindedness, and global teaching strategies. ^ The study was conducted at a public university in South Florida. A combination of quantitative and qualitative approaches was employed. Two groups of preservice social studies teachers were chosen as participants: a control group composed of 14 preservice teachers who enrolled in a global education class in the summer semester of 1998 and an experimental group that included nine preservice teachers who took the same class in the fall semester of 1998. The summer class was conducted in a traditional format, which included lectures, classroom discussions, and student presentations. The fall class incorporated a five-week Internet-based communication project. The Global Mindedness Scale (Hett, 1993) and an adapted Test of Global Knowledge (ETS, 1981) were administered upon the completion of the class. ^ Contrasting case studies were utilized to investigate the impact of participation in the ICONS on the development of preservice teachers' global pedagogy. Four preservice teachers, two selected from each group were observed and interviewed to explore how they were infusing global perspectives into social studies curriculum and instruction during a 10-week student teaching internship in the spring semester of 1999. ^ This study had three major findings. First, preservice social studies teachers from the experimental group on average scored significantly higher than those from the control group on the global knowledge test. Second, no significant difference was found between the two groups in their mean scores on the Global Mindedness Scale. Third, all four selected preservice social studies teachers were infusing global perspectives into United States and world history curriculum and instruction during their student teaching internship. Using multiple resources was the common pedagogy. The two who participated in the ICONS were more aware of using the communication feature of the Internet and the web sites that reflect more international perspectives to facilitate teaching about the world. ^ Recommendations were made for further research and for preservice studies teacher education program development. ^

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

The influence of balanced and imbalanced resource supply on biodiversity – functioning relationship across ecosystems

Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity-ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity-ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity-productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity-functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.

The influence of balanced and imbalanced resource supply on biodiversity – functioning relationship across ecosystems

Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity-ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity-ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity-productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity-functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.