Resource-constrained project scheduling: Notation, classification, models, and methods

There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.

http://web.nchu.edu.tw/pweb/users/arborfish/lesson/8681.pdf

An integrated survey of deterministic project scheduling

Communication in data-parallel applications often involves a collection of parallel flows. Traditional techniques to optimize flow-level metrics do not perform well in optimizing such collections, because the network is largely agnostic to application-level requirements. The recently proposed coflow abstraction bridges this gap and creates new opportunities for network scheduling. In this paper, we address inter-coflow scheduling for two different objectives: decreasing communication time of data-intensive jobs and guaranteeing predictable communication time. We introduce the concurrent open shop scheduling with coupled resources problem, analyze its complexity, and propose effective heuristics to optimize either objective. We present Varys, a system that enables data-intensive frameworks to use coflows and the proposed algorithms while maintaining high network utilization and guaranteeing starvation freedom. EC2 deployments and trace-driven simulations show that communication stages complete up to 3.16X faster on average and up to 2X more coflows meet their deadlines using Varys in comparison to per-flow mechanisms. Moreover, Varys outperforms non-preemptive coflow schedulers by more than 5X.

/pdf/efficient-coflow-scheduling-with-varys-3epdlqbhir.pdf

Efficient coflow scheduling with Varys

A network flow method is outlined for solving the linear programming problem of computing the least cost curve for a project composed of many individual jobs, where it is assumed that certain jobs must be finished before others can be started. Each job has an associated crash completion time and normal completion time, and the cost of doing the job varies linearly between these extreme times. Given that the entire project must be completed in a prescribed time interval, it is desired to find job times that minimize the total project cost. The~method solves this problem for all feasible time intervals.

A Network Flow Computation for Project Cost Curves

Among the major problems facing technical management today are those involving the coordination of many diverse activities toward a common goal. In a large engineering project, for example, almost all the engineering and craft skills are involved as well as the functions represented by research, development, design, procurement, construction, vendors, fabricators and the customer. Management must devise plans which will tell with as much accuracy as possible how the efforts of the people representing these functions should be directed toward the project's completion. In order to devise such plans and implement them, management must be able to collect pertinent information to accomplish the following tasks:(1) To form a basis for prediction and planning(2) To evaluate alternative plans for accomplishing the objective(3) To check progress against current plans and objectives, and(4) To form a basis for obtaining the facts so that decisions can be made and the job can be done.

https://www.mosaicprojects.com.au/PDF/PM-History_Critical_Path_Planning_&_Scheduling_Kelley_and_Walker_1959.pdf

Morgan R. Walker

Papers

Critical-path planning and scheduling

Critical-Path Planning and Scheduling