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
Public R&D project portfolio selection problem with cancellations
Date
2017-07-01
Author
ÇAĞLAR, Musa
Gürel, Sinan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
200
views
0
downloads
Cite This
In this study, we address a public R&D project portfolio selection problem with project cancellations. For several reasons, a funded R&D project may be halted before finishing the planned research. When a project is canceled, most of its budget is usually unused and also some of the spendings can return to the funding organization. In the call-based R&D programs, usually project selection decisions are made in one go, and, in the current call, it is not possible to award new projects with the unused budget. Decision-makers (DMs) of funding organizations can benefit from considering possible project cancellation situations to improve the budget utilization. We consider two cases. In the first case, we assume that cancellation probability of a project cannot be assessed but the DM can estimate the number of projects that will be canceled. In the second case, we assume that for each project, a cancellation probability can be assessed. For the first problem, we develop a mixed-integer linear programming formulation and a dynamic programming algorithm. For the second problem, we develop a chance-constrained stochastic programming formulation that can be solved as a mixed-integer second-order cone program. Our computational results show that practical-size problems can be solved by the proposed solution approaches.
Subject Keywords
Management Science and Operations Research
URI
https://hdl.handle.net/11511/37339
Journal
OR SPECTRUM
DOI
https://doi.org/10.1007/s00291-016-0468-5
Collections
Department of Industrial Engineering, Article
Suggestions
OpenMETU
Core
A resource investment problem with time/resource trade-offs
Colak, Erdem; Azizoğlu, Meral (Informa UK Limited, 2014-05-01)
In this study, we consider a Resource Investment Problem with time/resource trade-offs in project networks. We assume that there is a single renewable resource and the processing requirement of an activity can be reduced by investing extra resources. Our aim is to minimize the maximum resource usage, hence, the total amount invested for the single resource, while meeting the pre-specified deadline. We formulate the problem as a mixed integer linear model and find optimal solutions for small-sized problem in...
Capacity allocation problem in flexible manufacturing systems: branch and bound based approaches
ÖZPEYNİRCİ, SELİN; Azizoğlu, Meral (Informa UK Limited, 2009-01-01)
This study considers an operation assignment and capacity allocation problem that arises in flexible manufacturing systems. The machines have limited time and tool magazine capacities and the available tools are limited. Our objective is to maximise total weight of assigned operations. We develop a branch and bound algorithm that finds the optimal solutions and a beam search algorithm that finds high quality solutions in polynomial time.
A Lagrangean relaxation based approach for the capacity allocation problem in flexible manufacturing systems
ÖZPEYNİRCİ, SELİN; Azizoğlu, Meral (Informa UK Limited, 2010-05-01)
This study considers the operation assignment and capacity allocation problem in flexible manufacturing systems. A set of operations is selected to be processed and assigned to the machines together with their required tools. The purchase or usage of the required tools incurs a cost. The machines have scarce time and tool magazine capacities. The objective is to maximize the total weight of the assigned operations minus the total tooling costs. We use Lagrangean relaxation approach to obtain upper and lower...
Public R&D project portfolio selection problems under expenditure uncertainty and sectoral budget balancing
Çağlar, Musa; Gürel, Sinan; Department of Industrial Engineering (2016)
In this dissertation, we deal with the two issues that exist in the practice of public R&D funding program management. First one is the underutilization of the funding budget owing to several sources of expenditure uncertainty. Project cancellations and spending uncertainty of successfully completed projects cause to funding budget underutilization. In the first and second part of the dissertation, we propose new approaches to enhance the utilization of the total funding budget. Specifically, in the first p...
Flexible assembly line design problem with fixed number of workstations
Barutcuoglu, Sirin; Azizoğlu, Meral (Informa UK Limited, 2011-01-01)
In the paper, we study a flexible assembly line design problem with equipment decisions. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no smaller task time. Given the cycle time and number of workstations we aim to find the assignment of tasks and equipment to the workstations so as to minimise the total equipment cost. We develop a branch and bound algorithm that uses powerful lower bounds and reduction mechanisms. Our computational ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. ÇAĞLAR and S. Gürel, “Public R&D project portfolio selection problem with cancellations,”
OR SPECTRUM
, pp. 659–687, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37339.