Optimization and its related solving methods are becoming increasingly important in most academic and industrial fields. The goal of the optimization process is to make a system or a design as effective and functional as possible. This is achieved by optimizing a set of objectives while meeting the system requirements. Optimization techniques are classified into exact and approximate algorithms. Nature-inspired (NI) methods, a sub-class of approximate techniques, are widely recognized for providing efficient approaches for solving a wide variety of real-world optimization problems. In this paper, we discuss many scenarios where we can or cannot use different NI methods in tackling real-world optimization problems. We also enrich our survey with many studies for the reader to prove the efficiency and efficacy of using NI methods to tackle many real-world applications. Therefore, NI methods should be considered as alternative reliable approaches in the absence of exact methods to provide satisfactory solutions.

https://link.springer.com/content/pdf/10.1007/s43069-021-00068-x.pdf

Review on Nature-Inspired Algorithms

Information flow exchange within highly distributed, co-located, self-organising and networked projects is critical for successful planning, and ultimately, for successful infrastructure project de...

The analysis of information flow interdependencies within projects

Soil liquefaction is one of recognized nonlinear devastating types of ground failures associated with earthquakes. The analyses frameworks for this phenomenon have been addressed using different methods and correlated triggering factors in case histories. In the current paper, a hybrid model using imperialistic competitive metaheuristic algorithm (ICA) incorporated with multi-objective generalized feedforward neural network (MOGFFN) for the purpose of liquefaction potential analysis was assessed. The optimum hybrid ICA-MOGFFN model was applied on a diversified database of 296 compiled case histories comprising nine of the most significant effective parameters on liquefaction. The result of ICA-MOGFFN model demonstrated for 3.01%, 2.09% and 7.46% progress in the success rates for the safety factor, liquefaction occurrence and depth of liquefaction. Accordingly, the conducted precision–recall curves showed 5.08%, 1.73% and 3.92% improvement compared to MOGFFN. Further evaluations using different statistical metrics represented superior progress in performance of hybrid ICA-MOGFFN. The capability of the developed method then was approved from observed agreement with other accepted procedures. The results implied that the developed hybrid model was a flexible and accurate enough tool that can effectively be applied for the liquefaction potential analyses. Using sensitivity analyses, the most and least effective inputs on the predicted liquefaction parameters were identified.

Liquefaction potential analysis using hybrid multi-objective intelligence model

Shortening the lead time for product development (PD) provides enterprises with a competitive advantage. Given the iterative nature of PD projects, two aspects are regularly considered to shorten t...

Faster or fewer iterations? A strategic perspective of a sequential product development project

The project duration can be shortened by overlapping construction activities. However, the continuous changing of the environment tends to cause problems such as rework and the failure of the overlapping plan. In order to solve these problems, communication strategies for the overlapping of dependent activities are first introduced and optimized from a revenue perspective. We first consider the different maturities of upstream activity before and after the overlapping, the downstream sensitivity which is decided by involving communication strategies, and the learning and error-correcting ability of workers. Then, the overlap and communication strategies are decided by calculating the maximum revenue using Monte Carlo simulation and MATLAB based on overlap cost, communication cost, rework cost, and reward amount. Finally, the algorithm and BIM are combined to provide a visual overlap plan and dynamic control platform framework. This research is valuable for practitioners as it provides a dynamic overlap plan which can maximize the revenue in changing the environment and ensure the duration of the project. This research also provides researchers a new insight into combining overlap problems and BIM technology.

/pdf/model-and-algorithm-for-dependent-activity-schedule-2ix7rruziu.pdf

Model and Algorithm for Dependent Activity Schedule Optimization Combining with BIM

The appropriate iteration process model is the basis for managing and optimizing the product development process. In this article, we attempt to introduce the concept of process effectiveness and p...

Simulation and optimization of overlapped iteration process with multi-coupled activities based on value analysis:

It is an important QFD decision problem to determine the engineering characteristics and their corresponding actual fulfillment levels. With the increasing complexity of actual engineering problems, the corresponding QFD matrixes become much huger, and the time spent on analyzing these matrixes and making decisions will be unacceptable. In this paper, a solution for efficiently solving the QFD decision problem is proposed. The QFD decision problem is reformulated as a mixed integer nonlinear programming (MINLP) model, which aims to maximize overall customer satisfaction with the consideration of the enterprises’ capability, cost, and resource constraints. And then an improved algorithm G-ICA, a combination of Imperialist Competitive Algorithm (ICA) and genetic algorithm (GA), is proposed to tackle this model. The G-ICA is compared with other mature algorithms by solving 7 numerical MINLP problems and 4 adapted QFD decision problems with different scales. The results verify a satisfied global optimization performance and time performance of the G-ICA. Meanwhile, the proposed algorithm’s better capabilities to guarantee decision-making accuracy and efficiency are also proved.

https://downloads.hindawi.com/journals/mpe/2016/2601561.pdf

An Efficient Imperialist Competitive Algorithm for Solving the QFD Decision Problem

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Simulation and optimization of overlapped iteration process with multi-coupled activities based on value analysis:

An Efficient Imperialist Competitive Algorithm for Solving the QFD Decision Problem