344 research outputs found
Genetic algorithm optimization for dynamic construction site layout planning
The dynamic construction site layout planning
(DCSLP) problem refers to the efficient placement and relocation
of temporary construction facilities within a dynamically
changing construction site environment considering
the characteristics of facilities and work interrelationships,
the shape and topography of the construction site, and the
time-varying project needs. A multi-objective dynamic optimization
model is developed for this problem that considers
construction and relocation costs of facilities, transportation
costs of resources moving from one facility to another or to
workplaces, as well as safety and environmental considerations
resulting from facilities’ operations and interconnections.
The latter considerations are taken into account in
the form of preferences or constraints regarding the proximity
or remoteness of particular facilities to other facilities
or work areas. The analysis of multiple project phases and
the dynamic facility relocation from phase to phase highly
increases the problem size, which, even in its static form,
falls within the NP (for Nondeterministic Polynomial time)-
hard class of combinatorial optimization problems. For this
reason, a genetic algorithm has been implemented for the
solution due to its capability to robustly search within a large
solution space. Several case studies and operational scenarios
have been implemented through the Palisade’s Evolver
software for model testing and evaluation. The results indicate
satisfactory model response to time-varying input data
in terms of solution quality and computation time. The model
can provide decision support to site managers, allowing
them to examine alternative scenarios and fine-tune optimal
solutions according to their experience by introducing desirable
preferences or constraints in the decision process
Facility layout planning. An extended literature review
[EN] Facility layout planning (FLP) involves a set of design problems related to the arrangement of the elements that shape industrial production systems in a physical space. The fact that they are considered one of the most important design decisions as part of business operation strategies, and their proven repercussion on production systems' operation costs, efficiency and productivity, mean that this theme has been widely addressed in science. In this context, the present article offers a scientific literature review about FLP from the operations management perspective. The 232 reviewed articles were classified as a large taxonomy based on type of problem, approach and planning stage and characteristics of production facilities by configuring the material handling system and methods to generate and assess layout alternatives. We stress that the generation of layout alternatives was done mainly using mathematical optimisation models, specifically discrete quadratic programming models for similar sized departments, or continuous linear and non-linear mixed integer programming models for different sized departments. Other approaches followed to generate layout alternatives were expert's knowledge and specialised software packages. Generally speaking, the most frequent solution algorithms were metaheuristics.The research leading to these results received funding from the European Union H2020 Program under grant agreement No 958205 `Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)'and from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-101344-B-I00 `Optimisation of zerodefectsproduction technologies enabling supply chains 4.0 (CADS4.0)'PĂ©rez-Gosende, P.; Mula, J.; DĂaz-Madroñero Boluda, FM. (2021). Facility layout planning. An extended literature review. International Journal of Production Research. 59(12):3777-3816. https://doi.org/10.1080/00207543.2021.189717637773816591
Overview of Multi-Objective Optimization Approaches in Construction Project Management
The difficulties that are met in construction projects include budget issues, contractual time constraints, complying with sustainability rating systems, meeting local building codes, and achieving the desired quality level, to name but a few. Construction researchers have proposed and construction practitioners have used optimization strategies to meet various objectives over the years. They started out by optimizing one objective at a time (e.g., minimizing construction cost) while disregarding others. Because the objectives of construction projects often conflict with each other, single-objective optimization does not offer practical solutions as optimizing one objective would often adversely affect the other objectives that are not being optimized. They then experimented with multi-objective optimization. The many multi-objective optimization approaches that they used have their own advantages and drawbacks when used in some scenarios with different sets of objectives. In this chapter, a review is presented of 16 multi-objective optimization approaches used in 55 research studies performed in the construction industry and that were published in the period 2012–2016. The discussion highlights the strengths and weaknesses of these approaches when used in different scenarios
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