Project scheduling under undertainty – survey and research potentials.

The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. However, in the real world, project activities are subject to considerable uncertainty, that is gradually resolved during project execution. In this survey we review the fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, stochastic GERT network scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. We discuss the potentials of these approaches for scheduling projects under uncertainty.Management; Project management; Robustness; Scheduling; Stability;

A MULTI-OBJECTIVE MODEL FOR TIME–COST–QUALITY–RISK TRADE-OFF PROBLEMS IN PROJECT MANAGEMENT

This study presents a weighted four-dimensional time-cost-quality-risk trade-off problem to assist decision-makers in planning the best possible use of resources. The proposed model aims to minimize time and cost while maximizing quality and safety and to ensure that the project is completed as required. The critical path method was used to calculate the completion time, the analytical hierarchy process method was used to determine the weights of the quality parameters, and the 3T risk assessment method was used to calculate the risk values. The algorithm was coded in GAMS and optimized using CPLEX. A construction project with a deadline of 310 days, a budget of 5,250,000 ₺, 88% quality and a safety index (SI) of 77% was selected to analyze the accuracy of the model. The model achieved a solution with a completion time of 310 days, costs amounting to 5,247,775 ₺, 88.036% quality, and 77.338% SI

Time-cost-quality trade-off analysis for construction projects

The main objective of construction projects is to finish the project according to an available budget, within a planned schedule, and achieving a pre-specified extent of quality. Therefore, time, cost, and quality are considered the most important attributes of construction projects. The purpose of this study is to incorporate quality into the traditional two-dimensional time-cost trade-off (TCT) in order to develop an advanced three-dimensional time-cost-quality trade-off (TCQT) approach. Time, cost, and quality of construction projects are interrelated and have impacts on each other. It is a challenging task to strike a balance among these three conflicting objectives of construction projects since no one solution can be optimal for the three objectives. The overall performance of a project regarding time, cost, and quality is determined by the duration, cost, and quality of its activities. These attributes of each activity depend on the execution option by which the activity’s work is completed. It is required to develop an approach that is capable of finding an optimal or near optimal set of execution options for the project’s activities in order to minimize the project’s total cost and total duration, while its overall quality is maximized. For the aforementioned purpose, three various Microsoft Excel based TCQT models have been developed as follows: • First, a simplified model is developed with the objective of optimizing the total duration, cost, and quality of simple construction projects utilizing the GA-based Excel add in Evolver. • Second, a stochastic model is developed with the objective of optimizing the total duration, cost, and quality of construction projects applying the PERT approach in order to consider uncertainty associated with the performance of execution options and the whole project. • Third, an advanced multi objective optimization model is developed utilizing a self-developed optimization tool having the following capabilities: 1. Selecting an appropriate execution option for each activity within a considered project to optimize the objectives of time, cost, and quality. 2. Considering the discrete nature of duration, cost, and quality of various options for executing each activity. 3. Applying three various optimization approaches, which are the Goal Programming (GP), the Modified Adaptive Weight Approach (MAWA), and the Non-dominated Sorting Genetic Algorithms (NSGAII). 4. Analyzing both TCT and TCQT problems. 5. Considering finish-to-finish, start-to-start, and start-to-finish dependency relationships in addition to the traditional finish-to-start relationships among activities. 6. Considering any number of successors and predecessors for activities. 7. User-friendly input and output interfaces to be used for large-scale projects. To validate the developed models and demonstrate their efficiency, they were applied to case studies introduced in literature. Results obtained by the developed models demonstrated their effectiveness and efficiency in analyzing both TCT and TCQT problems

An integer linear programming model including time, cost, quality, and safety

Time, cost, quality and safety, are the four critical elements that contribute to project success. Traditionally, literature has focused on analysing only time and cost. Subsequently, other multi-objective optimization methods developed to optimize time, cost, quality or safety have been developed. New types of contracting methods designed by governments, included maximizing construction quality while minimizing its time and cost. Recently, due to the fact that the construction industry suffers from more accidents of greater severity than other industrial sectors, safety has become one of the four critical elements that contribute to project success. The project scheduling literature largely concentrates on the generation of a precedence and resource feasible schedule that optimizes the scheduling objective and that should serve as a baseline schedule for executing the project. However, these models do not allow to analyse alternative work plans that consider the trade-offs between time, cost, quality, and safety. In this paper, an integer linear programming problem is applied to a decision-CPM network in order to obtain an overall optimum including time, cost, quality and safety in a road building project. Using this type of model, the effects of alternative methods of performing the tasks can be considered and a greater degree of interaction between the planning and scheduling phases of a project is obtained

Application of expert systems in project management decision aiding

The feasibility of developing an expert systems-based project management decision aid to enhance the performance of NASA project managers was assessed. The research effort included extensive literature reviews in the areas of project management, project management decision aiding, expert systems technology, and human-computer interface engineering. Literature reviews were augmented by focused interviews with NASA managers. Time estimation for project scheduling was identified as the target activity for decision augmentation, and a design was developed for an Integrated NASA System for Intelligent Time Estimation (INSITE). The proposed INSITE design was judged feasible with a low level of risk. A partial proof-of-concept experiment was performed and was successful. Specific conclusions drawn from the research and analyses are included. The INSITE concept is potentially applicable in any management sphere, commercial or government, where time estimation is required for project scheduling. As project scheduling is a nearly universal management activity, the range of possibilities is considerable. The INSITE concept also holds potential for enhancing other management tasks, especially in areas such as cost estimation, where estimation-by-analogy is already a proven method

Time-Cost Tradeoff and Resource-Scheduling Problems in Construction: A State-of-the-Art Review

Duration, cost, and resources are defined as constraints in projects. Consequently, Construction manager needs to balance between theses constraints to ensure that project objectives are met. Choosing the best alternative of each activity is one of the most significant problems in construction management to minimize project duration, project cost and also satisfies resources constraints as well as smoothing resources. Advanced computer technologies could empower construction engineers and project managers to make right, fast and applicable decisions based on accurate data that can be studied, optimized, and quantified with great accuracy. This article strives to find the recent improvements of resource-scheduling problems and time-cost trade off and the interacting between them which can be used in innovating new approaches in construction management. To achieve this goal, a state-of-the-art review, is conducted as a literature sample including articles implying three areas of research; time-cost trade off, constrained resources and unconstrained resources. A content analysis is made to clarify contributions and gaps of knowledge to help suggesting and specifying opportunities for future research

The Use of Intelligent Systems for Planning and Scheduling of Product Development Projects

AbstractThe paper investigates the use of intelligent systems to identify the factors that significantly influence the duration of new product development. These factors are identified on the basis of an internal database of a production enterprise and further used to estimate the duration of phases in product development projects. In the paper, some models and methodologies of the knowledge discovery process are compared and a method of knowledge acquisition from an internal database is proposed. The presented approach is dedicated to industrial enterprises that develop modifications of previous products and are interested in obtaining more precise estimates for project planning and scheduling. The example contains four stages of the knowledge discovery process including data selection, data transformation, data mining, and interpretation of patterns. The example also presents a performance comparison of intelligent systems in the context of variable reduction and preprocessing. Among data mining techniques, artificial neural networks and the fuzzy neural system are chosen to seek relationships between the duration of project phase and other data stored in the information system of an enterprise