Critical Sequences and Resource Links Optimization in Resource-Constrained Project Scheduling

2018 ◽  
Vol 35 (05) ◽  
pp. 1850032
Author(s):  
Wan-An Cui

In order to identify critical activities and critical sequences under resource availability constraints, resource dependencies need to be established. By doing this, project managers and practitioners can focus their limited energy on specific activities and paths during the execution of a project schedule, thus guaranteeing that the project gets finished on time and with the available resources. This study proposes various rules to judge the superiority or inferiority of the methods of dependencies’ creation. The total number of critical sequences which is one of these rules, directly influences the degree of difficulty in controlling the whole project — a major concern for project managers. This study classifies activities in a resource-constrained project schedule on the basis of the relationships between activities and develops the basic idea behind the optimization of resource dependencies. Specifically, two mathematical models to minimize the total number of critical sequences and that of resource links through the table translation method are proposed. A computation example shows great improvement in the number of critical sequences, critical activities and resource links and gives effective results while solving the problems in the previous research. Moreover, simulations using J30, J60, and J120 instances by Kolisch highlight the high computing speed when searching for the actual minimum number of critical sequences and resource links thanks to the table translation method.

2021 ◽  
Vol 11 (2) ◽  
pp. 650
Author(s):  
Muritala Adebayo Isah ◽  
Byung-Soo Kim

Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.


Author(s):  
Yongyi Shou ◽  
Wenjin Hu ◽  
Changtao Lai ◽  
Ying Ying

A multi-agent optimization method is proposed to solve the preemptive resource-constrained project scheduling problem in which activities are allowed to be preempted no more than once. The proposed method involves a multi-agent system, a negotiation process, and two types of agents (activity agents and schedule agent). The activity agents and the schedule agent negotiate with each other to allocate resources and optimize the project schedule. Computational experiments were conducted using the standard project scheduling problem sets. Compared with prior studies, results of the proposed method are competitive in terms of project makespan. The method can be extended to other preemptive resource-constrained project scheduling problems.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pejman Rezakhani

PurposeDespite the extensive research in project risk management and availability of several techniques and tools, quantifying uncertainty in project schedules remains a challenge. Current risk analysis models suffer from several shortcomings that need to be addressed to provide more reliable and valid schedules. This paper aims to present a dynamic decision support system with the purpose of providing project managers with necessary tool for making real-time informed decisions.Design/methodology/approachThe proposed approach incorporates the widely accepted critical path method (CPM) calculations in a Bayesian network (BN). BN is employed to conduct inferencing and causal analysis and provide probabilistic results, which can improve the decision-making process. Time parameters of each activity in the CPM network is modeled by a set of simulation nodes in the BN. Prior probability distribution of activities duration is extracted from experts using a fuzzy analytical solution.FindingsThe model proposed in this paper is able to address some key outstanding issues of current project scheduling techniques through: (1) modeling the causality among different sources of schedule uncertainty, (2) minimizing uncertainty in experts' evaluations, (3) assessing effects of unknown risk factors and (4) using actual activity data for learning the behavior of project and predicting crew productivity.Originality/valueThe purposed methodology provides a framework for the new generation of project schedule analysis tools that are better informed by available knowledge and data, and hence, more reliable and useful.


2021 ◽  
Vol 11 (12) ◽  
pp. 5531
Author(s):  
Linlin Xie ◽  
Yajiao Chen ◽  
Ruidong Chang

Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.


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