Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Resource Constrained Multi-project Scheduling: Application in Software Company
Date
2019-01-01
Author
Kurt, Pelin Akyil
KEÇECİ, BARIŞ
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
473
views
0
downloads
Cite This
Project scheduling is a common problem of today's companies, which have project type production system. Project scheduling is a mechanism to communicate what tasks need to get done and which organizational resources will be allocated to complete those tasks in what timeframe. In this study, it is aimed to find the shortest completion time of projects and the starting/ending time of each activity as well in a software company, which is running simultaneous projects including multiple activities with predecessors under limited resources. The linear programming formulations in the literature are searched to solve the scheduling problem. The considered model is coded in OPL (Optimization Programming Language). The CPLEX solver engine is used to find the best solution of the coded formulation. In order to facilitate the execution of the project scheduling activities at the company, a computer application in the JAVA programming language is developed. This application also helps to generate the OPL code of the model and as well as to solve the model. In this way, it is possible for the employees to direct the basic scheduling activities more accurately, quickly and efficiently.
Subject Keywords
Resource constraint scheduling
,
Project management
,
Integer programming
,
Decision support
URI
https://hdl.handle.net/11511/64698
DOI
https://doi.org/10.1007/978-3-319-94196-7_51
Collections
Unclassified, Conference / Seminar
Suggestions
OpenMETU
Core
Multi-Project Multi-Resource Leveling Using Mixed Integer Programming
Altun, Murat; Sönmez, Rifat; Akçamete Güngör, Aslı (2018-11-16)
In construction projects, resource leveling aims to provide efficient resource planning during project implementation by reducing possible fluctuations in resource usage. Decision makers mostly focus on the single project to optimize its resource usage by applying various objective functions of resource leveling problem. However, in real life, multiple projects may be performed in the same time period. Hence, leveling the resources of each project separately generates sub-optimal solutions since interaction...
Hybrid meta-heuristic algorithms for the resource constrained multi-project scheduling problem
Uysal, Furkan; Sönmez, Rifat; Department of Civil Engineering (2014)
The general resource constrained multi-project scheduling problem (RCMPSP) consists of simultaneous scheduling of two or more projects with common resource constraints, while minimizing duration of the projects. Critical Path Method and other scheduling methods do not consider resource conflicts and practically used commercial project management software packages and heuristic methods provide very limited solutions for the solution of the RCMPSP. Considering the practical importance of multi-project schedul...
Hybrid Optimization Method for Large-Scale Multimode Resource-Constrained Project Scheduling Problem
Sönmez, Rifat (2016-11-01)
Despite many research efforts that have focused on the multimode resource-constrained project scheduling problem (MRCPSP), very little success has been achieved in solving the problem for large-scale projects. In this paper a new hybrid optimization method is presented to achieve an advancement in optimal planning and scheduling of large-scale construction projects with multiple duration/resource execution modes and resource constraints. The proposed method consists of a novel heuristic and unique genetic o...
Common Practices and Problems in Effort Data Collection in the Software Industry
Özkaya Eren, Ayşegül; Demirors, Onur (2011-11)
Effort data is crucial for project management activities in software projects. This data is utilized in estimations that are required for project planning, in the formation of benchmarking data sets and as a main input for project monitoring and control activities. However, there are known problems regarding effort data collection in the industry. In this study we investigate the effort data collection practices in the industry and factors that lead to inaccurate effort data collection. A pilot study was co...
Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling
BETTEMİR, ÖNDER HALİS; Sönmez, Rifat (American Society of Civil Engineers (ASCE), 2015-09-01)
Resource-constrained project scheduling problem (RCPSP) is a very important optimization problem in construction project management. Despite the importance of the RCPSP in project scheduling and management, commercial project management software provides very limited capabilities for the RCPSP. In this paper, a hybrid strategy based on genetic algorithms, and simulated annealing is presented for the RCPSP. The strategy aims to integrate parallel search ability of genetic algorithms with fine tuning capabili...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
P. A. Kurt and B. KEÇECİ, “Resource Constrained Multi-project Scheduling: Application in Software Company,” 2019, vol. 793, p. 549, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64698.
