Research on priority rules for the stochastic resource constrained multi-project scheduling problem with new project arrival

The resource constrained multi-project scheduling problem (RCMPSP) is a general and classic problem, which is usually considered and solved in a deterministic environment. However, in real project management, there are always some unforeseen factors such as one or more new project arrivals that give rise to intermittent changes in the activity duration (or stochastic duration) of the current project in execution by inserting the new project. This study takes two practical factors in terms of stochastic duration of project activities and new project arrivals waiting for insertion into account of the problem space to form a stochastic resource constrained multi-project scheduling problem with new project arrivals (SRCMPSP-NPA). Based on the benchmark of the PSPLIB (Project Scheduling Problem Library), a new data set is built and 20 priority rules (PRs) are applied to solve the problem and their performances are analyzed. In addition, a heuristic hybrid method is designed for solving the problem timely by dividing the entire scheduling process into multi-state scheduling problems solved by the corresponding rules separately. This approach has been verified by experiments and its performance is better than that of a single rule in most situations

Climbing depth-bounded adjacent discrepancy search for solving hybrid flow shop scheduling problems with multiprocessor tasks

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The problem even in its simplest form is NP-hard in the strong sense. The great deal of interest for this problem, besides its theoretical complexity, is animated by needs of various manufacturing and computing systems. We propose a new approach based on limited discrepancy search to solve the problem. Our method is tested with reference to a proposed lower bound as well as the best-known solutions in literature. Computational results show that the developed approach is efficient in particular for large-size problems

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance

The Project Scheduling Problem with Non-Deterministic Activities Duration: A Literature Review

Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration. Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved. Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends. Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.Peer Reviewe

Multi-project scheduling with 2-stage decomposition

A non-preemptive, zero time lag multi-project scheduling problem with multiple modes and limited renewable and nonrenewable resources is considered. A 2-stage decomposition approach is adopted to formulate the problem as a hierarchy of 0-1 mathematical programming models. At stage one, each project is reduced to a macro-activity with macro-modes resulting in a single project network where the objective is the maximization of the net present value and the cash flows are positive. For setting the time horizon three different methods are developed and tested. A genetic algorithm approach is designed for this problem, which is also employed to generate a starting solution for the exact solution procedure. Using the starting times and the resource profiles obtained in stage one each project is scheduled at stage two for minimum makespan. The result of the first stage is subjected to a post-processing procedure to distribute the remaining resource capacities. Three new test problem sets are generated with 81, 84 and 27 problems each and three different configurations of solution procedures are tested

Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach

Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.Peer Reviewe

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 heuristic methodology for solving spatial aresource-constrained project scheduling problems.

In this paper we present a heuristic methodology for solving resource-constrained project scheduling problems with renewable and spatial resources. We especially concentrate on spatial resources that are encountered in construction projects, but our analysis can easily be generalized to other sectors. Our methodology is based on the application of a schedule generation scheme on apriority list of activities. We explain why the parallel schedule generation scheme is not applicable for projects with spatial resources. We introduce a procedure for transforming priority lists into precedence and resource feasible lists that avoid deadlocks on the spatial resources. We conclude from a computational experiment on two sets of instances that priority rules performing well for the regular resource-constrained project scheduling problem also perform well in the presence of spatial resources and allow to effectively solve large problems in very short CPU time.Construction; Resource-constrained project scheduling; Spatial resources; Heuristic; Project scheduling; Scheduling; Problems; Sector; Rules; Time;

New benchmark results for the resource-constrained project scheduling problem.

This paper reports on computational results obtained with an updated version of the branch-and-bound procedure previously developed by Demeulemeester and Herroelen (1992) for solving the resource-constrained project scheduling problem (RCPSP). The new code fully exploits the advantages of 32-bit programming provided by recent compilers running on platforms such as Windows NT and OS/2 : flat memory, increased addressable memory and fast program execution. We study the impact of three important variables on the computation time for the RCPSP: addressable computer memory, the search strategy (depth-first, best-first or hybrid) and the introduction of an improved lower bound. We compare the results obtained by a truncated branch-and-bound procedure with the results generated by the minimum slack time heuristic and report on the dependency of its solution quality on the alotted CPU time.Scheduling; Project scheduling; Advantages; Studies;