Fuzzy Activity Network Method for Project Scheduling Under Resource Constraints

2007 ◽  
Vol 11 (8) ◽  
pp. 914-921
Author(s):  
Luong Duc Long ◽  
◽  
Ario Ohsato
Keyword(s):  
Genetic Algorithm ◽  
Project Scheduling ◽  
Fuzzy Numbers ◽  
Resource Constraints ◽  
Project Schedule ◽  
Project Duration ◽  
Activity Network ◽  
Decision Variables ◽  
Network Method ◽  
Critical Chain

In this article, a fuzzy activity network method is developed for project scheduling under resource constraints. Trapezoidal fuzzy numbers are used for estimating uncertain durations of activities, and then these fuzzy numbers are replaced by suitable crisp durations for project scheduling under resource constraints. In the next step, the critical chain is identified for determining the project duration, and uncertainties associated with activities are addressed by using feeding/project buffers to protect the project schedule from disturbances. For minimizing project duration, the proposed method considers both the suitable crisp durations and the start times of activities as decision variables. Hence, a new procedure based on genetic algorithm and priority heuristics is also developed for efficiently determining these decision variables. Furthermore, the method also considers selecting the best possible relationships between activities to minimize project duration. The proposed method using buffers makes it possible to improve project scheduling under resource constraints.

scholarly journals Scheduling Optimization of Prefabricated Construction Projects by Genetic Algorithm

2021 ◽  
Vol 11 (12) ◽  
pp. 5531
Author(s):  
Linlin Xie ◽  
Yajiao Chen ◽  
Ruidong Chang
Keyword(s):  
Project Scheduling ◽  
Construction Projects ◽  
Resource Constraints ◽  
Construction Project ◽  
Engineering Application ◽  
Project Schedule ◽  
Scheduling Optimization ◽  
Implementation Method ◽  
Traditional Construction ◽  
Construction Project Scheduling

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.

scholarly journals A Critical Design Structure Method for Project Schedule Development under Rework Risks

2019 ◽  
Vol 11 (24) ◽  
pp. 7229
Author(s):  
Guofeng Ma ◽  
Jianyao Jia ◽  
Tiancheng Zhu ◽  
Shan Jiang
Keyword(s):  
Resource Constraints ◽  
Project Schedule ◽  
Management Tools ◽  
Simulation Methodology ◽  
Schedule Management ◽  
Critical Design ◽  
Design Structure ◽  
Activity Sequence ◽  
Impact Area ◽  
Critical Chain

In order to overcome the difficulty in quantifying rework by traditional project schedule management tools, this study proposes an innovative method, namely improved Critical Chain Design Structure Matrix (ICCDSM). From the perspective of information flow, the authors firstly make assumptions on activity parameters and interactions between activities. After that, a genetic algorithm is employed to reorder the activity sequence, and a banding algorithm with consideration of resource constraints is used to identify concurrent activities. Then potential criticality is proposed to measure the importance of each activity, and the rework impact area is implicated to indicate potential rework windows. Next, two methods for calculating project buffer are employed. A simulation methodology is used to verify the proposed method. The simulation results illustrate that the ICCDSM method is capable of quantifying and visualizing rework and its impact, decreases iterations, and improves the completion probability. In this vein, this study provides a novel framework for rework management, which offers some insights for researchers and managers.

A New Genetic Algorithm for the RCPSP in Large Scale

2013 ◽  
Vol 4 (2) ◽  
pp. 29-40 ◽  
Author(s):  
Hossein Zoulfaghari ◽  
Javad Nematian ◽  
Nader Mahmoudi ◽  
Mehdi Khodabandeh
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Project Scheduling ◽  
Large Scale ◽  
Resource Constraints ◽  
Research Area ◽  
New Method ◽  
Scheduling Problem ◽  
Academic Problem ◽  
Project Scheduling Problem

The Resource Constrained Project Scheduling Problem (RCPSP) is a well-studied academic problem that has been shown to be well suited to optimization via Genetic Algorithms (GA). In this paper, a new method will be designed that would be able to solve RCPSP. This research area is very common in industry especially when a set of activities needs to be finished as soon as possible subject to two sets of constraints, precedence constraints and resource constraints. The presented algorithm in this paper is used to solve large scale RCPSP and improves solutions. Finally, for comparing, results are reported for the most famous classical problems that are taken from PSPLIB.

scholarly journals A DSM-Based CCPM-MPL Representation Method for Project Scheduling under Rework Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Guofeng Ma ◽  
Ming Wu ◽  
Keke Hao ◽  
Shanshan Shang
Keyword(s):  
Information Flow ◽  
Project Scheduling ◽  
Project Schedule ◽  
Design Structure ◽  
Flow Interactions ◽  
Critical Chain Project Management ◽  
Management Method ◽  
Representation Method ◽  
Relationship Of ◽  
Critical Chain

Rework risks caused by information flow interactions have become a major challenge in project scheduling. To deal with this challenge, we propose a model integrating the critical chain project management method, design structure matrix method, and max-plus method. Our model uses a start-to-start relationship of activities instead of the traditional finish-to-start relationship, which also allows overlaps between activities. We improve the accuracy of the rework safety time in two ways: (1) the overall overlapping effect is taken into consideration when calculating the rework time of an activity arising from the information flow interaction of its multiple predecessors overlapped with it; (2) the rework time arising from activity overlaps, the first rework time, and the second rework time are calculated as components of the rework safety time in our model, while the last one is ignored in traditional methods. Furthermore, the accuracy of time buffers is improved based on the improved rework safety time. Finally, we design the max-plus method to generate project schedules and appropriately sized time buffers. The empirical results show that the project schedule generated by the proposed method has a higher on-time completion probability, as well as more appropriately sized project buffers.

scholarly journals Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem

2021 ◽  
Vol 13 (17) ◽  
pp. 9956
Author(s):  
Osman Hürol Türkakın ◽  
David Arditi ◽  
Ekrem Manisalı
Keyword(s):  
Resource Allocation ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Priority Rules ◽  
Resource Constrained ◽  
Start Time ◽  
Project Duration ◽  
Resource Constrained Project Scheduling ◽  
Finish Time ◽  
Positional Weight

Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits of different priority rules have not been discussed in the literature in sufficient detail. This study is a response to this research gap. It compares 17 heuristic priority rules and seeks the best performing heuristic priority rule. This is the first study ever that compares heuristic priority rules by considering combinations of variations in (1) resource allocation procedures, (2) number of activities, (3) number of resource constraints, and (4) resource supply levels. The objective is to understand the relative merits of heuristic rules used in solving the RCPS problem. The findings indicate that the “minimum late finish time” rule generates the shortest predicted project duration when used in parallel resource allocation, whereas the “minimum late start time”, “minimum late finish time”, and the “highest rank of positional weight 2” rules perform best in serial resource allocation. It was also found that parallel resource allocation is slightly superior to serial resource allocation in most instances.

scholarly journals Sustainability-Oriented Project Scheduling Based on Z-Fuzzy Numbers for Public Institutions

2021 ◽  
Vol 13 (5) ◽  
pp. 2801
Author(s):  
Dorota Kuchta ◽  
Ewa Marchwicka ◽  
Jan Schneider
Keyword(s):  
Human Resources ◽  
Project Scheduling ◽  
Fuzzy Numbers ◽  
Negative Influence ◽  
Public Institutions ◽  
Public Institution ◽  
Project Schedule ◽  
Material Consumption ◽  
New Approach ◽  
Infrastructure Project

A new approach to sustainable project scheduling for public institutions is proposed. The approach is based on experts’ opinions on three aspects of sustainability of project activities (human resources consumption, material consumption and negative influence on local communities), expressed by means of Z-fuzzy numbers. A fuzzy bicriterial optimization model is proposed, whose objective is to obtain a project schedule of an acceptable sustainability degree and of acceptable duration and cost. The model was inspired and is illustrated by a real-world infrastructure project, implemented in 2019 by a public institution in Poland.

Development of Hybrid Genetic Algorithms for the Resource Constrained Multi-Project Scheduling Problem

2005 ◽  
Author(s):  
Wenjian Liu ◽  
Jinghua Li
Keyword(s):  
Genetic Algorithm ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Hybrid Genetic Algorithm ◽  
Second Phase ◽  
Scheduling Problem ◽  
Priority Rules ◽  
Resource Constrained ◽  
Chromosome Representation ◽  
Project Scheduling Problem

In multi-project environment, multiple projects share and compete for the limited resources to achieve their own goals. Besides resource constraints, there exist precedence constraints among activities within each project. This paper presents a hybrid genetic algorithm to solve the resource-constrained multi-project scheduling problem (RCMPSP), which is well known NP-hard problem. Objectives described in this paper are to minimize total project time of multiple projects. The chromosome representation of the problem is based on activity lists. The proposed algorithm was operated in two phases. In the first phase, the feasible schedules are constructed as the initialization of the algorithm by permutation based simulation and priority rules. In the second phase, this feasible schedule was optimized by genetic algorithm, thus a better approximate solution was obtained. Finally, after comparing several different algorithms, the validity of proposed algorithm is shown by a practical example.

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