Project Time-Cost Analysis under Generalised Precedence Relations

2009 ◽  
Author(s):  
S. Sakellaropoulos ◽  
A.P. Chassiakos
Keyword(s):  
Cost Analysis ◽  
Time Cost ◽  
Precedence Relations

Project time–cost analysis under generalised precedence relations

2004 ◽  
Vol 35 (10-11) ◽  
pp. 715-724 ◽  
Author(s):  
S. Sakellaropoulos ◽  
A.P. Chassiakos
Keyword(s):  
Cost Analysis ◽  
Time Cost ◽  
Precedence Relations

Extending project time–cost analysis by removing precedence relationships and task streaming

2006 ◽  
Vol 24 (6) ◽  
pp. 529-535 ◽  
Author(s):  
Matthew J. Liberatore ◽  
Bruce Pollack-Johnson
Keyword(s):  
Cost Analysis ◽  
Time Cost ◽  
And Task

scholarly journals A Dynamic Knowledge Model of Project Time-Cost Analysis Based on Trend Modelling

2019 ◽  
Vol 28 (1) ◽  
pp. 18-28
Author(s):  
Karel Doubravský ◽  
Radek Doskočil ◽  
Mirko Dohnal
Keyword(s):  
Project Management ◽  
Differential Equations ◽  
Cost Analysis ◽  
Trend Analysis ◽  
Linear Equations ◽  
Linear Differential Equations ◽  
Time Cost ◽  
Personnel Costs ◽  
Past Behavior ◽  
Linear Differential

This paper investigates the application of trend quantifiers of project time-cost analysis as a tool for decision-making support in the project management. Practical project management-related problems are solved under information shortages. It means that methods of statistical analysis cannot be easily used as they are based on the law of large numbers of observations. Numbers are information intensive quantifiers. The least information intensive quantifier is a trend; its values are increasing, constant, decreasing. If a derivative cannot be quantified by a trend, then nothing is known and therefore nothing can be analyzed/predicted. For this reason, the trend model M was created. The model M is based on a degraded set of differential equations or heuristics. A trend analysis of the model M is an evaluation of the relevant discrete set of solutions/scenarios S. A trend reconstruction is an evaluation of the model M if a (sub)set of scenarios S is given. The paper studies linear reconstruction, i.e. the model M is a set of linear differential equations. The trend reconstruction is partially reverse process to trend analysis. A case study has 7 variables (e.g. Project duration, Direct personnel costs, Indirect personal costs etc.) and the reconstructed set of linear differential equations has 7 equations. The set of 243 scenarios is obtained if this reconstructed set of trend linear equations is solved. Any future or past behavior of the model M can be described by a sequence of obtained scenarios.

Longest path time-cost analysis of construction projects with generalised activity constraints

2006 ◽  
Vol 6 (3) ◽  
pp. 271-281 ◽  
Author(s):  
Athanasios P. Chassiakos
Keyword(s):  
Cost Analysis ◽  
Construction Projects ◽  
Time Cost ◽  
Longest Path

Real-Time Cost Analysis: Application in Early Intervention

1985 ◽  
Vol 9 (2) ◽  
pp. 98-104
Author(s):  
Daniel J. Macy ◽  
D. Sue Schafer
Keyword(s):  
Early Intervention ◽  
Cost Analysis ◽  
Real Time ◽  
Time Cost ◽  
Analysis Application

Micro time cost analysis of parallel computations

1991 ◽  
Vol 40 (5) ◽  
pp. 613-628 ◽  
Author(s):  
B. Qin ◽  
H.A. Sholl ◽  
R.A. Ammar
Keyword(s):  
Cost Analysis ◽  
Parallel Computations ◽  
Time Cost

scholarly journals Preprocessing the Discrete Time-Cost Tradeoff Problem with Generalized Precedence Relations

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
Hanying Wei ◽  
Zhixiong Su ◽  
Yuan Zhang
Keyword(s):  
Discrete Time ◽  
Large Scale ◽  
Polynomial Algorithm ◽  
Time Cost ◽  
Total Cost ◽  
Project Completion ◽  
Precedence Relations ◽  
Path Lengths ◽  
Time Float ◽  
Generalized Precedence Relations

This study investigates the deadline of the discrete time-cost tradeoff problem (DTCTP-D) with generalized precedence relations (GPRs). This problem requires modes to be assigned to the activities of a project such that the total cost is minimized and the total completion time and the precedence constraints are satisfied. Anomalies under GPRs are irreconcilable with many current theories and methods. We propose a preprocessing technology, an equivalent simplification approach, which is an effective method for solving large-scale complex problems. We first study a way to deal with the anomalies under GPRs, such as the reduce (increase) in project completion as a consequence of prolonging (shortening) an activity, and discover relationships between time floats and path lengths. Then, based on the theories, we transform the simplification into a time float problem and design a polynomial algorithm. We perform the simplification and improve the efficiency of the solution by deleting redundant calculation objects.

A Time-Cost Analysis of Teaching a Laparoscopic Entero-Enterostomy

2007 ◽  
Vol 64 (6) ◽  
pp. 342-345 ◽  
Author(s):  
David T. Harrington ◽  
G.D. Roye ◽  
Beth A. Ryder ◽  
Thomas J. Miner ◽  
Pamela Richardson ◽  
...  
Keyword(s):  
Cost Analysis ◽  
Time Cost ◽  
Analysis Of Teaching
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