scholarly journals An evolutionary stochastic discrete time-cost trade-off method

2019 ◽  
Vol 46 (7) ◽  
pp. 581-600 ◽  
Author(s):  
Bahaa Hussein ◽  
Osama Moselhi
Keyword(s):  
Large Scale ◽  
Implementation Strategies ◽  
Project Managers ◽  
Time Cost ◽  
Trade Off ◽  
Managerial Flexibility ◽  
Optimal Execution ◽  
Main Effect ◽  
Execution Mode ◽  
Selection Of

This study introduces a newly developed method for optimized time-cost trade-off under uncertainty. It identifies the optimal execution mode for each project activity that results in minimizing the overall project cost and (or) duration while satisfying a specified joint confidence level of both time and cost. The method uses an evolutionary-based algorithm along with a design generator of experiments and blocking techniques. The developed method accounts for managerial flexibility towards the selection of execution modes. This accommodates experience-based judgement of project managers in this process. Hence, the second fold of the developed method is a completely randomized experiment module that depicts the main effect of changing an activity mode on the project total cost and overall duration. The method provides the decision-maker a guideline for making well-informed implementation strategies. The results obtained demonstrate benefits and accuracy of the developed method and its applicability for large-scale projects.

Time-cost-quality-environmental impact trade-off resource-constrained project scheduling problem with DEA approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sayyid Ali Banihashemi ◽  
Mohammad Khalilzadeh
Keyword(s):  
Environmental Impacts ◽  
Cost Optimization ◽  
Project Managers ◽  
Time Cost ◽  
Quality Factors ◽  
Trade Off ◽  
Content Type ◽  
Execution Mode ◽  
Project Objectives ◽  
Efficient Execution

PurposeThe purpose of this paper is to evaluate project activities' efficiency in different execution modes for the optimization of time–cost-quality and environmental impacts trade-off problem.Design/methodology/approachThis paper presents a parallel Data Envelopment Analysis (DEA) method for evaluation of project activities with different execution modes to select the best execution mode and find a trade-off between objectives. Also, according to the nature of the project activities, outputs are categorized into desirable (quality) and undesirable (time, cost and environmental impacts) and analyzed based on the DEA model. In order to rank efficient execution modes, the ideal and anti-ideal virtual units method is used. The proposed model is implemented on a real case of a rural water supply construction project to demonstrate its validity.FindingsThe findings show that the use of the efficient execution mode in each activity leads to an optimal trade-off between the four project objectives (time, cost, quality and environmental impacts).Practical implicationsThis study help project managers and practitioners with choosing the most efficient execution modes of project activities taking time–cost-quality-environmental impacts into account.Originality/valueIn this paper, in addition to time and cost optimization of construction projects, quality factors and environmental impacts are considered. Further to the authors' knowledge, there is no method for evaluating project activities' efficiency. The efficiency of different activity modes is also evaluated for the first time to select the most efficient modes. This research can assist project managers with choosing the most appropriate execution modes for the activities to ultimately accomplish the project with the lowest time, cost and environmental impacts along with the highest quality.

scholarly journals Selection of construction machine by considering time-cost trade-off problem

2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Önder Halis Bettemir ◽  
◽  
Engin Özdemir ◽  
Didem Eren Sarıcı
Keyword(s):  
Time Cost ◽  
Trade Off ◽  
Construction Machine ◽  
Selection Of

scholarly journals Utility of Genetic Algorithms for Solving Large-Scale Construction Time-Cost Trade-Off Problems

2018 ◽  
Vol 32 (1) ◽  
pp. 04017072 ◽  
Author(s):  
Duzgun Agdas ◽  
David J. Warne ◽  
Jorge Osio-Norgaard ◽  
Forrest J. Masters
Keyword(s):  
Genetic Algorithms ◽  
Large Scale ◽  
Scale Construction ◽  
Time Cost ◽  
Construction Time ◽  
Trade Off

scholarly journals Bi-Objective Scheduling Optimization for Discrete Time/Cost Trade-Off in Projects

2018 ◽  
Vol 10 (8) ◽  
pp. 2802 ◽  
Author(s):  
Hongbo Li ◽  
Zhe Xu ◽  
Wenchao Wei
Keyword(s):  
Discrete Time ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Critical Path ◽  
Large Set ◽  
Time Cost ◽  
Trade Off ◽  
Project Duration ◽  
Computational Performance ◽  
Trade Offs

In sustainable project management, time and cost are two critical factors affecting the success of a project. Time/cost trade-offs in projects accelerate the execution of some activities by increasing the amount of non-renewable resources committed to them and therefore shorten the project duration. The discrete time/cost trade-off problem (DTCTP) has been extensively studied during the past 20 years. However, due to its complexity, the DTCTP—especially the DTCTP curve problem (DTCTP-C)—has only been solved for relatively small instances. To the best of our knowledge, there is no computational performance analysis for solving the DTCTP-C on large project instances with up to 500 activities. This paper aims to fill this gap. We present two bi-objective heuristic algorithms for the DTCTP-C where both project duration and cost are minimized. The objective is to obtain a good appropriate efficient set for the large-scale instances. The first algorithm is based on the non-dominated sorting genetic algorithm II (NSGA-II) and uses a specially designed critical path-based crossover operator. The second algorithm is a steepest descent heuristic which generates efficient solutions by iteratively solving the DTCTP with different deadlines. Computational experiments are conducted to validate the proposed algorithms on a large set of randomly generated problem instances.

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