Global ETD Search

11	Time-Cost Optimization of Large-Scale Construction Projects Using Constraint Programming Golzarpoor, Behrooz January 2012 (has links) Optimization of time and cost in construction projects has been subject to extensive research since the development of the Critical Path Method (CPM). Many researchers have investigated various versions of the well-known Time-Cost Trade-off (TCT) problem including linear, convex, concave, and also the discrete (DTCT) version. Traditional methods in the literature for optimizing time and cost of construction projects range from mathematical methods to evolutionary-based ones, such as genetic algorithms, particle swarm, ant-colony, and leap frog optimization. However, none of the existing research studies has dealt with the optimization of large-scale projects in which any small saving would be significant. Traditional approaches have all been applied to projects of less than 100 activities which are far less than what exists in real-world construction projects. The objective of this study is to utilize recent developments in computation technology and novel optimization techniques such as Constraint Programming (CP) to improve the current limitations in solving large-scale DTCT problems. Throughout the first part of this research, an Excel-based TCT model has been developed to investigate the performance of traditional optimization methods, such as mathematical programming and genetic algorithms, for solving large TCT problems. The result of several experimentations confirms the inefficiency of traditional methods for optimizing large TCT problems. Subsequently, a TCT model has been developed using Optimization Programming Language (OPL) to implement the Constraint Programming (CP) technique. CP Optimizer of IBM ILOG Optimization Studio has been used to solve the model and to successfully optimize several projects ranging from a small project of 18 activities to very large projects consisting of more than 10,000 activities. Constraint programming proved to be very efficient in solving large-scale TCT problems, generating substantially better results in terms of solution quality and processing speed. While traditional optimization methods have been used to optimize projects consisting of less than one hundred activities, constraint programming demonstrated its capability of solving TCT problems comprising of thousands of activities. As such, the developed model represents a significant improvement in optimization of time and cost of large-scale construction projects and can greatly enhance the level of planning and control in such projects. Optimization Constraint Programming Project Management Time-Cost Trade-off Large-scale Construction Projects Decision Support Tools Management Sciences
12	The Budget Constrained Discrete Time/cost Trade-off Problem In Project Networks Degirmenci, Guvenc 01 August 2008 (has links) (PDF) The time/cost trade-off models in project management aim to compress the project completion time by accelerating the activity durations at an expense of additional resources. The budget problem in discrete time/cost trade-off scheduling selects the time/cost mode -among the discrete set of specified modes- for each activity so as to minimize the project completion time without exceeding the available budget. There may be alternative modes that solve the budget problem optimally, however each solution may have a different total cost value. In this study we aim to find the minimum cost solution among the optimal solutions of the budget problem. We analyze the structure of the problem together with its linear programming relaxation and derive some mechanisms for reducing the problem size. We solve the reduced problem by linear programming relaxation and branch and bound based approximation and optimization algorithms. We find that our branch and bound algorithm finds optimal solutions for medium-sized problem instances in reasonable times and the approximation algorithms produce high quality solutions. We also discuss the way our algorithms could be used to construct the time/cost trade-off curve. Q General Science 1-385
13	Time-Cost Optimization of Large-Scale Construction Projects Using Constraint Programming Golzarpoor, Behrooz January 2012 (has links) Optimization of time and cost in construction projects has been subject to extensive research since the development of the Critical Path Method (CPM). Many researchers have investigated various versions of the well-known Time-Cost Trade-off (TCT) problem including linear, convex, concave, and also the discrete (DTCT) version. Traditional methods in the literature for optimizing time and cost of construction projects range from mathematical methods to evolutionary-based ones, such as genetic algorithms, particle swarm, ant-colony, and leap frog optimization. However, none of the existing research studies has dealt with the optimization of large-scale projects in which any small saving would be significant. Traditional approaches have all been applied to projects of less than 100 activities which are far less than what exists in real-world construction projects. The objective of this study is to utilize recent developments in computation technology and novel optimization techniques such as Constraint Programming (CP) to improve the current limitations in solving large-scale DTCT problems. Throughout the first part of this research, an Excel-based TCT model has been developed to investigate the performance of traditional optimization methods, such as mathematical programming and genetic algorithms, for solving large TCT problems. The result of several experimentations confirms the inefficiency of traditional methods for optimizing large TCT problems. Subsequently, a TCT model has been developed using Optimization Programming Language (OPL) to implement the Constraint Programming (CP) technique. CP Optimizer of IBM ILOG Optimization Studio has been used to solve the model and to successfully optimize several projects ranging from a small project of 18 activities to very large projects consisting of more than 10,000 activities. Constraint programming proved to be very efficient in solving large-scale TCT problems, generating substantially better results in terms of solution quality and processing speed. While traditional optimization methods have been used to optimize projects consisting of less than one hundred activities, constraint programming demonstrated its capability of solving TCT problems comprising of thousands of activities. As such, the developed model represents a significant improvement in optimization of time and cost of large-scale construction projects and can greatly enhance the level of planning and control in such projects. Optimization Constraint Programming Project Management Time-Cost Trade-off Large-scale Construction Projects Decision Support Tools Management Sciences
14	Investigating the Cost of National School Lunch Program Lunches versus the Full, Time-Inclusive Cost of Home-Packed Lunches O'Keefe, Keely Ryan 23 March 2018 (has links) Background: National School Lunch Program (NSLP) meals have been found to be of higher dietary quality than home-packed lunches. Objective: To explore the cost, including time, of NSLP versus different categories of home-packed lunches. Methods: Data from pre-kindergarten and kindergarten lunches from three schools in southwest Virginia were used for this study. Each lunch item was priced, and a direct cost was assigned based on the lunches contents. Time assessments were conducted to determine the amount of time to prepare each lunch, with a monetary value for time computed based on average salary of the respective county. A non-parametric Kruskal Wallis test was used to compare the direct cost, time, time cost, and the full cost of the meals. Medians were computed based on outlier data. Results: The lowest median direct cost was found for homemade packed lunches ($1.55), followed by homemade school lunches ($2.11), then convenience packed lunches ($2.12), and then NSLP lunches ($2.15). When incorporating preparation time, the NSLP lunch cost the least ($2.15), followed by convenience packed lunches ($2.56), then homemade packed lunches ($2.92), and then homemade school lunches ($11.32). Seventy-six percent (n=414) of home-packed lunches contained sugar-sweetened beverages and/or dessert food items, accounting for almost one-quarter (21.8%) of the cost of all home-packed lunches. Conclusion: When time is computed as part of the total cost of NSLP versus home-packed lunches, the NSLP is the least expensive option. In conjunction with the nutritional benefits of the NSLP, this time-cost data may help shift purchasing and consumption patterns. / Master of Science National School Lunch Program NSLP home-packed lunch direct cost time cost time-inclusive cost full cost
15	Optimal Scope Of Work For International Integrated Systems Ertem, Mustafa Alp 01 June 2005 (has links) (PDF) This study develops a systems integration project scheduling model which identifies the assignment of activity responsibilities that minimizes expected project implementation cost, considering the project risk. Assignment of resources to the individual jobs comprising the project is a persistent problem in project management. Mostly, skilled labor is an essential resource and both the time and the cost incurred to perform a job depend on the resource to which job is assigned. A systems integration project includes implementation issues in the areas of shipping, installation, and commissioning. Implementation problems lead to project delays, increased costs, and decreased performance, leading to customer dissatisfaction with the systems integrator. Activities can be performed in one of three ways: by the integrator, by the customer, or jointly between the integrator and customer. In this study we select the performer (mode) of each activity comprising the project network while taking into consideration the varying cost, duration and extreme event probability of each activity among different modes-integrator, joint work and customer. Use of the model will permit customers and integrators to mutually agree on an appropriate assignment of responsibilities in the contract. Systems integrators can also use the model to improve their implementation services offerings. An experimental design and a Monte-Carlo simulation study were conducted to see the effects of the parameters of the problem on the selection of modes. Q General Science 1-385
16	Hierarchical multi-project planning and supply chain management : an integrated framework Pakgohar, Alireza January 2014 (has links) This work focuses on the need for new knowledge to allow hierarchical multi-project management to be conducted in the construction industry, which is characterised by high uncertainty, fragmentation, complex decisions, dynamic changes and long-distance communication. A dynamic integrated project management approach is required at strategic, tactical and operational levels in order to achieve adaptability. The work sees the multi-project planning and control problem in the context of supply chain management at main contractor companies. A portfolio manager must select and prioritise the projects, bid and negotiate with a wide range of clients, while project managers are dealing with subcontractors, suppliers, etc whose relationships and collaborations are critical to the optimisation of schedules in which time, cost and safety (etc) criteria must be achieved. Literature review and case studies were used to investigate existing approaches to hierarchical multi-project management, to identify the relationships and interactions between the parties concerned, and to investigate the possibilities for integration. A system framework was developed using a multi-agent-system architecture and utilising procedures adapted from literature to deal with short, medium and long-term planning. The framework is based on in-depth case study and integrates time-cost trade-off for project optimisation with multi-attribute utility theory to facilitate project scheduling, subcontractor selection and bid negotiation at the single project level. In addition, at the enterprise level, key performance indicator rule models are devised to align enterprise supply chain configuration (strategic decision) with bid selection and bid preparation/negotiation (tactical decision) and project supply chain selection (operational decision). Across the hierarchical framework the required quantitative and qualitative methods are integrated for project scheduling, risk assessment and subcontractor evaluation. Thus, experience sharing and knowledge management facilitate project planning across the scattered construction sites. The mathematical aspects were verified using real data from in-depth case study and a test case. The correctness, usefulness and applicability of the framework for users was assessed by creating a prototype Multi Agent System-Decision Support System (MAS-DSS) which was evaluated empirically with four case studies in national, international, large and small companies. The positive feedback from these cases indicates strong acceptance of the framework by experienced practitioners. It provides an original contribution to the literature on planning and supply chain management by integrating a practical solution for the dynamic and uncertain complex multi-project environment of the construction industry. 658.7
17	GRCPSP Robusto basado en Producción para Proyectos de Edificación y Construcción Ponz Tienda, José Luis 20 September 2010 (has links) Esta Tesis doctoral representa una nueva formulación del problema del GRCPSP (Generalized Resource-Constrained Project Scheduling Problem) mediante grafos PDM (Precedence Diagramming Method) con fragmentación en entornos realistas, donde las tareas son diferenciadas entre productivas y no productivas y las dependencias entre ellas no se limitan a los ya clásicos valores de dependencia, sino que se incorpora un nuevo concepto de relación de producción, apareciendo relaciones basadas en un cierto nivel de producción necesario de otra tarea para poder comenzar, o cierta producción que quedará pendiente de finalizar una vez finalizada la tarea precedente. Este nuevo enfoque del problema basado en procesos productivos, no solo elimina las paradojas causadas por las tareas críticas inversas o críticas perversas, sino que nos permite aplicar conceptos tradicionales de la planificación de la producción como es la productividad variable ocasionada por el aprendizaje con las repercusiones que esto produce en las relaciones basadas en producción. Además se analizan las naturalezas de los recursos intervinientes en el proyecto, reformulando los costes asociados a los mismos y su repercusión sobre el nuevo modelo propuesto, permitiendo la aplicación de algoritmos de optimización TCTP (Time Cost Trade-Off Problem) que hasta ahora era inviable. Para finalizar se incorpora la borrosidad a los valores intervinientes en el proyecto presentando la formulación de un modelo robusto de planificación de la producción basada en grafos PDM que sirve de punto de partida a la resolución del GRCPSP en entornos realistas. / Ponz Tienda, JL. (2010). GRCPSP Robusto basado en Producción para Proyectos de Edificación y Construcción [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8540 / Palancia Pdm Precedence diagramming method Rcpsp Grcpsp Generalized precedence Time-cost Heuristic Project scheduling Splitting allowed Production planning Learning curve Construction scheduling Fuzzy scheduling CONSTRUCCIONES ARQUITECTONICAS ORGANIZACION DE EMPRESAS 1207 - Investigación operativa 330523 - Organización de obras 531203 - Construcción
18	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics
19	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics

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