Next Article in Journal
“Oh This Learning, What a Thing It Is!”—Putting Sustainability First in Teaching Techniques and in Content
Next Article in Special Issue
The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator
Previous Article in Journal
Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices
Previous Article in Special Issue
A Decision Framework under a Linguistic Hesitant Fuzzy Set for Solving Multi-Criteria Group Decision Making Problems
Open AccessArticle

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

by Hongbo Li 1, Zhe Xu 2 and Wenchao Wei 3,*
1
School of Management, Shanghai University, Shanghai 200444, China
2
School of Economics and Management, Beihang University, Beijing 100191, China
3
School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Sustainability 2018, 10(8), 2802; https://doi.org/10.3390/su10082802
Received: 5 July 2018 / Revised: 2 August 2018 / Accepted: 5 August 2018 / Published: 7 August 2018
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. View Full-Text
Keywords: bi-objective optimization; heuristics; discrete time/cost trade-off; project scheduling bi-objective optimization; heuristics; discrete time/cost trade-off; project scheduling
Show Figures

Figure 1

MDPI and ACS Style

Li, H.; Xu, Z.; Wei, W. Bi-Objective Scheduling Optimization for Discrete Time/Cost Trade-Off in Projects. Sustainability 2018, 10, 2802.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop