Este trabalho propõe uma heurística construtiva determinística e uma heurística construtiva probabilística para resolver o problema de programação de projetos com custo de disponibilidade de recursos e custo de penalidade por atraso no término do projeto (RACPT - Resource Availability Cost Problem with Tardiness). Os algoritmos combinam a flexibilidade da atividade com a flexibilidade do recurso para selecionar a próxima atividade a ser programada. A data de início de uma atividade é a data mais cedo em que sua execução não gera o maior pico de utilização dos recursos ou a data mais cedo na qual o custo total do projeto for menor. A melhor versão das heurísticas foi obtida após o teste de várias regras de prioridade, conforme a revisão bibliográfica realizada. As heurísticas propostas foram testadas em 360 instâncias de testes e seus resultados foram comparados aos obtidos pela formulação matemática baseada em strip packing e restrições disjuntivas implementada no programa CPLEX. A heurística construtiva determinística gera uma solução viável rapidamente, porém de baixa qualidade. Já a heurística construtiva probabilística gera soluções ótimas ou próximas da ótima para problemas pequenos ou para problemas fáceis e gera soluções muito melhores do que o CPLEX na metade do tempo computacional para os problemas médios e grandes ou para problemas difíceis. Dado os bons resultados obtidos e à implementação no programa VBA for Microsoft Excel, a heurística construtiva probabilística proposta é um método bom e prático para resolução do RACPT. / This work proposes a deterministic constructive heuristic and a probabilistic constructive heuristic for solving the resource availability cost problem with tardiness (RACPT). The algorithms combine the flexibility of an activity with the flexibility of a resource to select the next activity to be scheduled. The start time of the activity is the earliest date in which the activity\'s execution does not create resources usage peak or the earliest date with the lowest total project cost. We tested several priority rules according to the literature review and determined the best version of the heuristics. Afterwards, we tested the proposed heuristics in 360 instances and compared its results with the solutions obtained by the optimization software CPLEX. The RACPT implementation on CPLEX utilized a mathematical formulation based on strip packing concepts and disjunctive constraints. The computational results showed that the deterministic constructive heuristic generates feasible solutions of poor quality in low computational time. The probabilistic constructive heuristic achieved better results. For small instances or easy problems, it found optimal or near-optimal solutions. For medium and large instances or hard problems, it obtained better results than CPLEX in half-computational time. We believe that the probabilistic constructive heuristic is a good and practical method for solving the RACPT. The proposed algorithm produced good results in reasonable computational time and was implemented on the popular software VBA for Microsoft Excel.

O processo de produção, no ambiente da Construção Civil, é abordado segundo certos princípios gerenciais que absorvem conceitos vindo da Engenharia de Produção. Para obter a qualidade na produção, pelo critério competitivo que envolve prazos e confiabilidade de entrega, é fundamental a integração entre o projeto do produto e a produção através do projeto da produção. O processo de planejamento, no contexto do projeto da produção, requer o uso de ferramentas de suporte à tomada de decisão, fazendo da programação uma etapa essencial para o ganho de consistência deste processo decisório. A pesquisa trata da programação de projetos com limitação de recursos, a fim de encontrar uma boa solução para o problema de programação de forma simples e satisfatória. O método utiliza como ferramenta de apoio o software Microsoft Project para manipular os projetos com mais agilidade e flexibilidade, considerando as regras de prioridades que são usadas a depender dos critérios gerenciais adotados pelas empresas. O método é baseado na classe de procedimentos heurísticos: Job Oriented Heuristic Scheduling, já que o grau de prioridade dos projetos orienta o desenvolvimento da programação conjunta, denominada Programação multi-projetos. / The production process in the Civil Construction environment is approached according to some management principles that reinforce concepts from Production Engineering. To obtain Quality in production through the competitive criterion, which comprehends fast delivery time and on-time delivery, it is fundamental the integration between Product Design and production through Production Design. The planning process requires the use of procedures to support the decision-making process concerning global production systems in construction companies. Thus scheduling would be an essential stage for the acquisition of decision consistence. This dissertation deals with the resource-constrained Project Scheduling Problem using a heuristic method based on priority rules. Heuristic procedures are used to obtain a good solution to the problem in a practical and satisfactory way. The method uses Microsoft Project as a supporting tool to deal with the projects with more agility and flexibility. The priority rules are based on management criteria adopted by the companies. The method is based on the category of heuristic procedures known as Job Oriented Heuristic Scheduling, since the project priority degrees orient the steps of the multi-project scheduling.

This paper analyses the current state of research regarding solution methods dealing with resource-constrained project scheduling problems. The intention is to present a concentrated survey and brief scientific overview on models, their decision variables and constraints as well as current solution methods in the field of project scheduling. The allocation of scarce resources among multiple projects with different, conflicting decision variables is a highly difficult problem in order to achieve an optimal schedule which meets all (usually different) of the projects’ objectives. Those projects, e.g. the assembly of complex machinery and goods, consume many renewable, e.g. workforce/staff, and non-renewable, e.g. project budget, resources. Each single process within these projects can often be performed in different ways – so called execution modes can help to make a schedule feasible. On the other hand the number of potential solutions increases dramatically through this fact. Additional constraints, e.g. min/max time lags, preemption or specific precedence relations of activities, lead to highly complex problems which are NP-hard in the strong sense.

In project scheduling, the activity durations can often be reduced by dedicating additional resources. Time/Cost Trade-off Problem considers the compromise between the total cost and project duration. The discrete version of the problem assumes a number of time/cost pairs, so called modes, and selects a mode for each activity. In this thesis we consider the Discrete Time/Cost Trade-off Problem. We first study the Deadline Problem, i.e., the problem of minimizing total cost subject to a deadline on project duration. To solve the Deadline Problem, we propose several optimization and approximation algorithms that are based on optimal Linear Programming Relaxation solutions. We then analyze the problem of generating all efficient solutions, and propose an approach that uses the successive solutions of the Deadline Problem. Our computational results on large-sized problem instances have revealed the satisfactory behavior of our algorithms.

Resource constrained project scheduling problem (RCPSP) has been subject of extensive research in project management literature as RCPSP is one of the most challenging problems in the project management and is of great practical importance. In this thesis, resource allocation capabilities of Primavera Enterprise V.6.0-Project Management (P6) and MS Project 2007 (MS) were evaluated for solving overallocated problems in the RCPSP. Fourty-five resource overallocated instance projects were selected from the PSPLIB to evaluate performance of P6 and MS Project 2007. Three resource allocation priority rules of P6 and two resource allocation priority rules of MS were used for comparision. The best solutions of different priority rules for P6 and MS were compared by using t-test. Results of the P6 and MS were compared with the lower bounds and optimum solutions of the previous heuristic methods. The comparisions indicate that both P6 and MS has limited capabilities for solving overallocated problems in RCPSP. Especially for larger projects the widely used project management software packages can not provide optimum or near optimum solutions.

In this thesis, we consider a discrete time/cost trade-off problem with a single nonrenewable resource. We assume the resource is released at some prespecified time points and at some prespecified quantities. We also assume that the costs due to the activities are incurred at their completions. Our aim is to minimize total project completion time. We formulate the problem as a pure integer programming model. We show that the problem is strongly NP-hard. We find lower bounds by pure linear programming and mixed integer linear programming relaxations of the model. We develop three heuristic procedures using the optimal solutions of mixed integer linear program and pure linear program. The results of our computational study reveal the satisfactory performance of our heuristic procedures.

Inadequate or weak preparatory work before starting construction of any structure may cause serious problems during the construction period. For example, projects without sufficient detailed drawings or construction schedules and a disorganized building site can create many problems in the management and completion of the construction works. Consequently, the cost of construction increases digressively, the construction duration of the project extends and the quality of construction is affected adversely. This study dwells on the importance of construction schedules in achieving the aim of producing good quality construction work within the specified duration. Monitoring continuously the interactive relation concerning delays in construction schedules and contractor demands is a complicated process. Here the simplest and basic approach is that, both for owner and contractor, time is money and for this reason construction schedule delays should be analyzed and corrective measures should be taken in a timely manner. The main purpose of this study is to investigate the causes of construction schedule delays and the methods of schedule delay analyses. In this context completion construction works of a covered swimming pool building in Ankara was selected as a case study for analyzing project scheduling and the delays therein. The &ldquo / Time Impact Analysis Method&rdquo / (TIA) was applied to the case study project using PRIMAVERA&reg / software in order to determine the construction schedule delays / to measure the impacts of these delays on the project completion duration / and to allocate responsibility amongst the project participants for preventing delay claims. After the application of the delay analysis it was observed that the delays in the critical activities extended the project duration by 57 days in total i.e. by 15.4 % of the estimated construction period. Fines should have been paid by the contractor because of 31-days non-excusable delays. Also, the contractor should have been given a time extension of 26-days due to 22-days excusable compensable delays and 4-days excusable non-compensable delays which were beyond the control of the contractor. These delays were caused due to organizational deficiencies of the owner, the bureaucracy of the provincial municipality, the lack of detail drawings during the municipality application, the lack of experience of the contractor, problems in material procurement, unforeseeable weather conditions and shortages of qualified employees of the subcontractors. It was observed that of these all except one correspond to the important causes of delays as reported in literature concerning public projects in Turkey.

This dissertation examines a profit-maximizing project selection and scheduling problem. Assume that a set of potentially profitable projects are available, yet limited available resources may not allow all of them to be pursued. Profit profiles for projects are assumed to be non-increasing functions of project completion times, i.e. profit returns are sensitive to time-to-market. Decision needs to be made on which sub-set of projects should be chosen and how resources should be allocated to these projects such that the total profit is maximized.Formal mathematical models are formulated for various versions of the problem, including such ones incorporating a third team formation aspect. Structure of the problem is examined and insights are gained regarding prioritization of project, specifically. Although prioritization is sub-optimal in general, heuristic solution methods based on prioritization are pursued, since the scheduling sub-problem itself is NP-hard.A decomposition heuristic framework is first proposed to obtain good solutions using minimum computational time. Sets of test instances are generated using project network data from well-known source in the literature. Computational runs reveal that three priority rules achieve significantly better profits than the benchmarking random priority rule.Improving upon the prioritization based decomposition heuristic, an implicit enumeration is proposed. This algorithm does not examine all priority sequences, yet guarantees an optimal priority sequence when the computation is completed. Several fathoming rules are proposed to cut back computational time effectively. Comparison to the profits achieved by the best priority rule and the benchmarking random priority rule shows a significant improvement on profits, yet at a cost of reasonable added computation time.Future research areas include identifying general conditions under which prioritization of projects would lead us to an optimal solution. Developing better upper bounds for the implicit enumeration scheme is also of interest. The team formation aspect has yet to be treated computationally. It would also be of interest to consider how synergy deviation information may be fed back to the earlier stages of project selection and scheduling decision. Trade-off between profit and team synergy may also be considered in the future.

This thesis is about software project scheduling and use of earned value method on software projects. As a result of the study, a solution for software project scheduling problems is proposed. A mathematical formulation, developed using integer programming method, is at the heart of the solution. Objective of the formulation is to minimize the development costs consisting of direct labor cost, indirect costs and probable penalty costs. The formulation takes the capability and compatibility variances among resources into account whereas contemporary approaches mostly focus on resource availability. Formulation is of type discrete time and takes the time span to be searched as input. Therefore a heuristic approach has been developed for providing time span input to the models developed using the formulation. The heuristic approach has been proven to be calculating a time span that does not hinder achieving the absolute optimum schedule and shortens the solution time of the integer programs. The heuristic approach and problem formulation have been incorporated into a computer program that generates integer programs and heuristic solutions. This thesis also describes a method for preparing an earned value plan, based on the scheduling solution defined. The method aims to help project managers in determining the status of their projects and deciding whether any corrective action is required or not. Besides the method, approaches for incorporating indirect costs and penalty costs, which are not explicitly discussed in literature, into final cost estimation have been described.

Critical Chain Project Management (CCPM) is a project scheduling technique which has been developed to overcome some of the deficiencies of traditional methods and where, in a single project environment, the critical chain is the longest chain of activities in a project network, taking into account both activity precedence and resource dependencies. In multi-project environments, the constraint is the resource which impedes projects' earlier completion. CCPM relies on buffers to protect the critical chain and monitor/control the project. The literature review conducted by this study reveals that the research on CCPM principles in multi-project environments is still extremely scarce. The review also suggests that outright elimination of multitasking (i.e. switching back and forth among two or more concurrent tasks) by imposing a relay race mentality (i.e. starting a task as soon as it becomes available and finishing it as soon as possible), as one of the main features of CCPM, might worsen the resource constraints of CCPM portfolios and cause creation of over-protective buffers. It further implies that there is also a good level of multitasking that can benefit such environments by improving resource availability and requiring shorter protective buffers. This research aims to bridge the gap by investigating the impact of level of multitasking on resource availability issues and project and feeding buffer sizing in CCPM portfolios with different resource capacities. This is pursued through adopting a deductive approach and developing five research hypotheses, considering ten different levels of resource capacity, testing the hypotheses by conducting Monte Carlo simulations of randomly generated project data and comparing the results with deterministic duration values of the same portfolios with 30%, 40% and 50% feeding and project buffer sizes. In total, ten portfolios with similar size, variability and complexity levels, each containing four projects, were simulated. It was concluded that: firstly, some limited levels of multitasking, determined in relation to the level of resource capacity, can be beneficial to time performance of CCPM portfolios; secondly, shorter buffer sizes can be accounted for by abolishing the ban on multitasking while maintaining a lower rate of resource capacity; finally, the element of relay race work ethic that completely bans multitasking should not be implemented as it proved to be counterproductive in terms of resource availability. Seven recommendations and a buffer sizing framework are provided as complementary guidelines to practitioners' own experience, knowledge and judgment, in addition to an explanation of theoretical and practical contributions and suggestions for future research.