Cost minimization of locating construction machinery park with the use of simulation and optimization algorithms

Anysz, Hubert; Zawistowski, J.

doi:10.1051/matecconf/201819604088

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…The results of the analysis are presented in the form of the resulting probability distribution. Using the Monte Carlo simulation technique, for each examined factor a histogram is obtained for various scenarios of materialization of the identified risk factors of the project [11].…”

Section: Monte Carlo Methodsmentioning

confidence: 99%

Cash-Flow Schedules Optimization within Life Cycle Costing (LCC)

et al. 2020

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Investment and construction plans, architectural and construction decisions, and spatial and technology-related decisions made at the early stages of a project have a significant impact on meeting the investment goals and customer expectations. Decision making is a very time-consuming and complicated process (due to the complexity of construction processes). The whole difficulty comes to specifying the appropriate criteria for assessing the given activities, providing answers to the questions of the decision-making bodies. A set of appropriate criteria and mathematical tools (such as computer algorithms with multi-criteria analysis) can significantly improve and accelerate the decision-making process. This article combines ESORD (an IT tool that allows you to compare different types of solutions based on mathematical calculations) with the Monte Carlo method. The developed approach can help the investor to optimize their cash-flow schedule. The original method enables the client to select a construction project variant characterized by the best economical and sustainable parameters, while taking into account customers’ demands.

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Section: Monte Carlo Methodsmentioning

confidence: 99%

Cash-Flow Schedules Optimization within Life Cycle Costing (LCC)

et al. 2020

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“…Therefore, it is more appropriate to base the optimization criteria on the construction project cash flow analysis. According to the priorities of the contractor, the criteria of construction project cash flow optimization may include [22][23][24][25][26][27] the following:…”

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confidence: 99%

Cash Flow Optimization for Renewable Energy Construction Projects with a New Approach to Critical Chain Scheduling

et al. 2021

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This study concerns the use of the critical chain method to schedule the construction of renewable energy facilities. The critical chain method is recognized as a useful project management tool, transforming a stochastic problem of uncertainty in activity durations into a deterministic one. However, this method has some shortcomings. There are no clear principles of grouping non-critical activities into feeding chains. Another ambiguity is sizing the feeding buffers with regard to the topology of the network model and the resulting dependencies between activities, located in different chains. As a result, it is often necessary to arbitrarily adjust the calculated sizes of feeding buffers before inserting them into the schedule. The authors present the new approach to sizing the time buffers in the schedule, enabling a quick assessment of the quality of a given solution variant and finding a solution that best meets the established criteria, conditions, and constraints. The essence of the presented approach is the two-step sizing of time buffers with the use of deterministic optimization and stochastic optimization techniques. Taking into account construction management needs, the optimization criteria are based on the construction project cash flow analysis. The effectiveness of the presented approach is illustrated by an example of developing a wind power plant construction schedule. According to the results, the presented approach ensures the protection of the scheduled completion date of the construction and the stability of the schedule.

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Construction Cost Optimization System Based on AHP-BP Neural Network Algorithm

Zhang

2021

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

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Cost minimization of locating construction machinery park with the use of simulation and optimization algorithms

Cited by 4 publications

References 7 publications

Cash-Flow Schedules Optimization within Life Cycle Costing (LCC)

Cash-Flow Schedules Optimization within Life Cycle Costing (LCC)

Cash Flow Optimization for Renewable Energy Construction Projects with a New Approach to Critical Chain Scheduling

Construction Cost Optimization System Based on AHP-BP Neural Network Algorithm

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