A Discrete-Time Resource Allocated Project Scheduling Model

2021 ◽  
pp. 616-629
Author(s):  
Berkay Çataltuğ ◽  
Helin Su Çorapcı ◽  
Levent Kandiller ◽  
Fatih Kağan Keremit ◽  
Giray Bingöl Kırbaş ◽  
...  
Keyword(s):  
Discrete Time ◽  
Project Scheduling ◽  
Scheduling Model ◽  
Time Resource

scholarly journals Robust Proactive Project Scheduling Model for the Stochastic Discrete Time/Cost Trade-Off Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Hongbo Li ◽  
Zhe Xu ◽  
Li Xiong ◽  
Yinbin Liu
Keyword(s):  
Discrete Time ◽  
Project Scheduling ◽  
Programming Model ◽  
Optimization Theory ◽  
Mixed Integer ◽  
Time Cost ◽  
Activity Time ◽  
Interval Numbers ◽  
Trade Off ◽  
Scheduling Model

We study the project budget version of the stochastic discrete time/cost trade-off problem (SDTCTP-B) from the viewpoint of the robustness in the scheduling. Given the project budget and a set of activity execution modes, each with uncertain activity time and cost, the objective of the SDTCTP-B is to minimize the expected project makespan by determining each activity’s mode and starting time. By modeling the activity time and cost using interval numbers, we propose a proactive project scheduling model for the SDTCTP-B based on robust optimization theory. Our model can generate robust baseline schedules that enable a freely adjustable level of robustness. We convert our model into its robust counterpart using a form of the mixed-integer programming model. Extensive experiments are performed on a large number of randomly generated networks to validate our model. Moreover, simulation is used to investigate the trade-off between the advantages and the disadvantages of our robust proactive project scheduling model.

scholarly journals Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Mengqi Liu ◽  
Miyuan Shan ◽  
Juan Wu
Keyword(s):  
Project Scheduling ◽  
Simulation Experiment ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Scheduling Optimization ◽  
Scheduling Model ◽  
Make To Order ◽  
Swarm Algorithm ◽  
The One ◽  
Fierce Competition

For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.

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