Although deep learning algorithms have been widely used, their performance depends heavily on a good set of hyperparameters. This article presents an efficient Hyperband and trust-region-based mode-pursuing sampling hybrid method for hyperparameter optimization. First, Hyperband is modified and used to select the optimum quickly from a large number of random sampling points to construct a trust region

ABSTRACT In this article, the buckling optimization of axially functionally graded (AFG) columns to maximize the buckling capacity is studied. Consideration is given to an AFG column having a tapered regular polygon cross section and variable material properties. The governing differential equation is derived based on Euler–Bernoulli beam theory with the relevant boundary conditions and is solved using

The design of grade-separated road and railway crossings can be complicated and time-consuming since the intersection point as well as the road and rail alignments should jointly optimize an objective such as minimum construction costs. Moreover, the design of grade-separated road and railway crossings should consider additional crossing constraints and possible revisions of the road alignments. However

ABSTRACT Recent trends in path planning have led to a proliferation of studies that find solutions to the path planning problems in an unknown cluster environment. This study aims to find an optimum impact-free path length for a mobile robot with a multi-objective optimization approach. The multi-objective optimization problem is formulated by using path length and a safety aspect as the two objectives

ABSTRACT This article considers scheduling in tree data gathering networks. The worker nodes of a network acquire datasets of known sizes at possibly different times. The datasets are sent to intermediate nodes which process them and then pass the results to the base station. Each dataset is assigned a due date by which it should arrive at the base station. The scheduling problem is to minimize the

ABSTRACT Robust design optimization (RDO) of large-scale engineering systems is computationally intensive and requires significant CPU time. Considerable computational effort is still required within conventional meta-model assisted RDO frameworks. The primary objective of this article is to minimize further the computational requirements of meta-model assisted RDO by developing a global two-layered

Aircraft optimization design problems are mostly computationally intensive. These complicated problems probably contain mixed-variables, while most research has focused on continuous variables. This article sets up a mixed-variable surrogate-based optimization algorithm framework that includes a mixed-variable experiment design method and an inaccurate infilling method. The mixed-variable experiment

ABSTRACT Centrifugal pumps, being used nowadays for many applications, must be suited for a wide range of pressure ratios and flow rates. To overcome difficulties arising from the design and performance prediction of this class of turbomachinery, many researchers have proposed coupling Computation Fluid Dynamics (CFD) codes and optimization algorithms for fast and effective design procedures. However

ABSTRACT This article presents a method for multiobjective optimization of a complex system, modelling it as a collection of components and resource flows between them. Constraints can be imposed on a component basis or system-wide, based on the resource flows. Optimization is performed by a genetic algorithm utilizing a variable-length genome. This specialized genome enables a more open-ended design

ABSTRACT Uncertain differential equations with time-varying delay are a special type of uncertain functional differential equation. Stability in measure and stability in mean for this type of differential equation have been investigated. For the sake of completeness, this article explores the other two types of stability. Firstly, the concepts of the almost sure stability and the pth moment stability

ABSTRACT An optimization method of pattern synthesis is proposed for peak sidelobe level (PSLL) suppression and null controlling via element rotation and phase optimization. The purpose of this method is to introduce the rotation angle of element into the anti-interference array design to further improve the radiation performance. The design objective is to suppress the PSLL while maximizing the main-beam

In this article, optimization of the toroidal tuned liquid column damper (TTLCD) for suppressing harmonic vibration is investigated. First, a closed-form solution for the TTLCD–structure system is derived. Based on the solution, optimization is carried out and some design tables listing the optimum parameters are obtained. Secondly, a parametric investigation of key parameters that affect the damping

ABSTRACT In this work, an analytical solution to temperature field distribution in a finite cylinder body caused by constant-strength, periodic-motion heat sources is obtained. Two heat source models, i.e. single and multiple, are proposed. The analytical solution is applied in calculating the temperature rise of a Z-direction feeding ball screw. The plotted temperature rise curves show that the error

The article proposes a multi-objective optimization method called Generalized Differential Evolution (GDE3) for a Variable Number of Dimensions (VND). The well-known generalized differential evolution is adapted to handle problems where the number of decision space variables is not a priori known. The performance of the method is assessed on a set of benchmark problems based on standard multi-objective

ABSTRACT This article presents a novel mathematical formulation to solve the problem of optimally sizing and managing battery energy storage for the solar photovoltaic system integration of a multi-apartment building. The aim is the maximization of the collective self-consumption maintaining control over time of the energy sold and bought and the monitoring of the state of batteries while ranging from

ABSTRACT To effectively optimize low-thrust many-revolution transfer trajectories to geostationary Earth orbit (GEO), this article proposes a novel metamodel-based low-thrust GEO transfer optimization scheme. A simplified control law is used to convert the optimal low-thrust transfer problem into a parameter optimization problem, where the gains of control law are optimized to determine the time-minimum

ABSTRACT This article proposes a design method to minimize the compliance or maximize the fundamental natural frequency of continuum structures under thin feature and support structure constraints in additive manufacturing processes. The objective functions are, respectively, to minimize the compliance of continuum structures under static loads and maximize the fundamental natural frequency of vibrating

This article develops a multi-resolution topology optimization (MTOP) approach based on the solid isotropic material with penalization (SIMP) method, which is effective in obtaining high-resolution designs at low computational cost. The extended finite element method (XFEM) is employed to decouple the analysis mesh, material description and nodal design variables. By the advantage of XFEM at modelling

Structural optimization is an important tool for structural designers that helps them to find innovative design solutions and structural forms with a better exploitation of materials as well as decreased self-weight and minimum material costs. In this article, a design procedure coupling the influence matrix method and genetic algorithms to optimize stay cables in cable-stayed bridges is presented

ABSTRACT In this article, the multi-modal and multi-route transportation problem for hazardous materials under uncertainty is studied, and an interval 0–1 integer programming model is proposed to optimize the transportation risks and transportation costs during the transportation of hazardous materials. Factors such as freight rates and loading and unloading costs are different when the transportation

ABSTRACT A deep-learning approach is proposed to predict an optimized high-resolution structure with multi-boundary conditions. An enhanced deep super-resolution (SR) neural network and a convolutional neural network are constructed and trained to establish the mapping relationship between low- and high-resolution structures for the topology optimization problem. The data set for training and testing

ABSTRACT Coated structures are structures with a solid thin-walled coating enclosing substrates. Coated structures with porous substrates (infills) are often adopted in additive manufacturing to reduce the material cost and printing time, while improving robustness against local bucking, unknown loads and material deficiencies. This article presents a new density filter method for the topology optimization

(2020). Correction. Engineering Optimization. Ahead of Print.

In Jordan, the waste collection process incurs high transportation and operation costs. The main reasons for the high transportation costs are inefficient clustering and poor routing systems. In response, this research proposes a mathematical model for optimal clustering of garbage containers or bins (referred to as customers) for solid waste collection. The model’s objective function is to define

ABSTRACT This article considers unrelated parallel processor scheduling problems with deterioration effects and processor maintenance activities. In this case, deterioration occurs during processing. A maintenance activity on a parallel processor is allowed after a job is processed, and the maintenance time is a fixed constant. After the maintenance work is completed, the processor is restored to the

This article proposes a deterministic model for a post-disaster scenario in an urban emergency medical services system to allocate the emergency vehicles to the patients and transfer them to the hospital. To solve the model, an exact approach called the -constraint method is applied to the problem. Since this problem belongs to the class of NP-hard problems, two metaheuristic algorithms, namely the

By fully utilizing the designability of semi-rigid connections in precast concrete structures, the gradient-based interior point algorithm is applied to perform a two-stage optimization with the objectives of minimum material cost and a target interstorey drift ratio distribution. To obtain an efficient storey lateral stiffness estimate for optimization, the modified Muto’s method is further extended

ABSTRACT In this article, topology optimization of transient nonlinear heat conduction problems is solved by a parameterized level-set method. Nonlinear density-based and continuum shape sensitivity analyses are conducted for topology generation and shape optimization. Meanwhile, the backward time transient adjoint structures are derived. To suppress dependence of the initial guess for the parameterized

ABSTRACT High-resolution topology optimization ensures highly accurate solutions and structural details; however, it also imposes a heavy computational burden. In this study, an efficient topology optimization method based on Cube-Tet mesh is proposed that significantly shortens the duration of finite element analysis (FEA) by compressing the size of the sparse matrix. First, the uniform cubic voxel

The optimal reactive power dispatch (ORPD) problem, as a subproblem of optimal power flow, has significant effects in providing reliability and economic operation. In this article, a modified version of the pathfinder algorithm (PFA), which is inspired by the collective movement of a swarm led by one member, is proposed for solving the ORPD problem. The objective of this study is to minimize the power

The demands for a high-performance prosthesis include high strength and low weight. This study addresses the optimization of a new tube concept, made of composite material, which makes use of an isogrid and internal layer. For the methodological procedure, a response surface methodology (RSM) was used to define in what quantity, under what conditions and which data should be collected during a given

ABSTRACT Integrating production scheduling with transportation decisions is an important problem that is receiving increasing interest from the logistics industry. As an order is received, the manufacturer starts planning its production while considering the appropriate decisions for delivery. The company can adopt an auction paradigm to involve external occasional drivers, besides using its own fleet

ABSTRACT The concurrent optimization of powertrain component parameters and energy management strategy for a hybrid hydraulic vehicle (HHV) is the key to implementing improved fuel economy while satisfying driving performance criteria. In this article, which considers coupled parameters and conflicting objectives in the optimization, an improved multi-objective particle swarm optimization (IMOPSO)

ABSTRACT In today’s competitive environment, industrial units are seeking to reduce costs and increase customer numbers; if their business involves perishable products, achieving these goals is even more important. By integrating scheduling and vehicle routing problems for perishable products, this study tries to minimize costs and maximize customers’ purchase probability. In the scheduling stage,

ABSTRACT In this work, a topology optimization (TO) based framework for functional grading of triply periodic minimal surfaces (TPMS) based lattice structures is developed, implemented and demonstrated. Material interpolation laws of the gyroid, G-prime and Schwarz-D surfaces are derived by numerical homogenization for transversely isotropic elasticity and are represented as convex combinations of

Despite numerous studies on vibration reduction techniques for mechanical systems, the expensive computational cost is still a challenging issue for complex structures with a huge number of degrees of freedom. A constructing method of global reduced-order basis (ROB) is proposed in this article by combining proper orthogonal decomposition (POD) with an iterative process. The POD method is adopted to

ABSTRACT An interval robust optimization method is suggested to improve the robustness and performance of the process or product in design. A general uncertain robust optimization problem is considered in which the objective function and constraints are both nonlinear and uncertain, and the uncertainties of design variables and uncertain parameters are all included and depicted by the interval model

This article introduces a novel constraining approach for structural optimization that aims to support the conceptual engineer during the early embodiment phase for structural lightweight design. It reduces the time spent on structural engineering studies by enabling optimization algorithms to detect geometric intersections by analysing the mesh information. This article reviews approaches from the

Computational efficiency in simulation-based optimization algorithms is essential when the system objective functions are expensive to evaluate and computational resources are limited. This article proposes a hybrid Bayesian BFGS algorithm (HB2O) to address this efficiency problem. An adaptive expected improvement (AEI) acquisition function is developed to realize a self-adaptive sampling strategy

ABSTRACT Experimental optimization of physical and biological processes is a difficult task. To address this, sequential surrogate models combined with search algorithms have been employed to solve nonlinear high-dimensional design problems with expensive objective function evaluations. In this article, a hybrid surrogate framework was built to learn the optimal parameters of a diverse set of simulated

In systems with many components that are required to be constantly active, such as refineries, predicting the components that will break in a time interval after a stoppage may significantly increase their reliability. However, predicting the set of components to be repaired is a challenging task, especially when several conditions (e.g. breakage probability, repair time and cost) have to be considered

From the perspective of bionics, a structural topology optimization method combining a bone remodelling algorithm and real engineering requirements is proposed. Through joint simulation using MATLAB and Ansys, this method uses explicit physical concepts and efficient computer solving capabilities, which makes it highly practical and simple. The effectiveness and feasibility of the method are verified

This article investigates the cooperative task planning problem of heterogeneous multi-robot systems in an order picking warehouse, with challenging characteristics such as heterogeneous agents, interrelated utilities and complex intertask dependencies. These characteristics bring great challenges for modelling and optimization of the problem. This study establishes a novel mapping mechanism to describe

In the production process of open-pit mines, transportation costs account for 45–60% of the total cost. Therefore, a reasonable and economic transportation system can effectively improve production efficiency. In this article, optimization of the layout of the fixed crushing station in the in-pit crusher and conveyor system of open-pit mining is studied. First, the entire ore body is discretized into

The failure probability-based global sensitivity index (FPGSI) analyses how the model inputs affect the failure probability of a model. It is useful for guiding reliability-based design optimization and enhancing reliability by controlling the uncertainty of the important input variables. Based on the law of total variance in successive intervals without overlapping and the dual-stage adaptive kriging

An enhanced permutation search (EPS) algorithm is proposed for stacking sequence optimization of simply supported orthotropic plates to maximize the buckling load. By taking advantage of the approximate linear superposition regular of buckling load factor and accounting for the nonlinear effects of buckling mode as well as the non-dimensional anisotropic coefficients, the stacking sequence design is

The purpose of this article is to develop numerical models for topology optimization of sandwich panels subjected to impact loads. Numerical models account for the effects of energy absorption capability and impact load resistant capacity on the development of optimal designs. A topology optimization technique based on the evolutionary structural optimization method and nonlinear dynamic finite element

Many engineering design problems are associated with computationally expensive and time-consuming simulations for design evaluation. In such problems, each candidate design should be selected carefully, even though it means extra algorithmic complexity. This study develops the Proximity-based Surrogate-Assisted Evolutionary Algorithm (PSA-EA) that aims at handling both single-objective and multi-objective

Surrogate models have been widely used for Reliability-Based Design Optimization (RBDO) to solve complex engineering problems. However, the accuracy and efficiency of surrogate-based RBDO largely rely on the sample size and sampling methods. For this reason, successive sampling methods that update the surrogate successively are more promising. Nowadays, several Kriging-based RBDO approaches have been

Social group optimization (SGO) is a human-based metaheuristic optimization technique which shows accurate results for different benchmark functions but has not been studied for civil engineering structural health monitoring problems. This article deals with the use of SGO for damage analysis of different modelled civil engineering structures and a real-life American Society of Civil Engineers (ASCE)

This article develops a hub-and-spoke architecture for a parcel delivery system using a network that includes a distribution centre and several cross-dock facilities. Several real-world assumptions, including an electric truck fleet, mobile charging station, third-party logistics, capacity constraints, last-mile deliveries and customer dissatisfaction, are incorporated in this problem. Besides, because

The experience-based learning (EBL) algorithm is a new global optimization algorithm that is free from any algorithm-specific control parameters and has been applied to solve structural damage identification problems. However, similar to other metaheuristic algorithms, the EBL algorithm has its disadvantages. To obtain better searching performance, a modified EBL algorithm is proposed for solving the

Parameter selection during the construction of surrogates is often conducted by minimizing the Mean Squared Cross-Validation Error (MSE-CV). Surrogates constructed using MSE are poorly optimized using gradient-based optimizers. Hence, Nelder–Mead like optimizers are often favoured, which is unfortunate as surrogates make analytical gradients freely available and gradient-based optimizers scale better

The accurate determination of postblast ore boundaries can significantly help to control ore loss and dilution in opencast mines. Determining the boundaries is difficult using methods other than direct and expensive blast-induced rock movement monitoring, so many mines directly use the preblast ore boundary to guide the shovel. A new postblast ore boundary determination method using a soft computing

Chassis technical specifications such as durability and ride comfort are the focuses during vehicle development projects. Additionally, robustness is also important as it is related to manufacturing costs as well as chassis performance in the total life cycle. This article proposes a robust multi-objective optimization approach to improve chassis specifications while taking the physical random factors

This article addresses the m-machine no-wait flowshop scheduling problem with the objective of minimizing makespan subject to an upper bound on total completion time. An iterated greedy-with-local-search algorithm is proposed and compared with a mathematical model and the best method found in the literature for solving this problem. Computational experiments and statistical analysis are conducted to

The two-machine flowshop scheduling problem to minimize total completion time with separate set-up times is addressed. Set-up times are modelled as uncertain within an interval where only the lower and upper bounds are known. Eighty-one different versions of a newly developed constructive algorithm are proposed. Computational experiments to evaluate the performance of the proposed algorithm are conducted

In this article, a model of a T-shaped fin, consisting of a set of ordinary differential equations (ODEs), is considered. The purpose of this article is to numerically solve ODE systems of a T-shaped fin (there is no reported exact and analytical solution) using an alternative approach. Utilizing a base approximation function, some mathematical principles and metaheuristics, an approximate solution

Topology Optimization (TO) redistributes the material within a design space to optimize certain objective functions under given constraints. Currently available TO methods do not consider the designer's preferences about the final material layout in the optimized design. Contrarily, often an improved design similar to a reference design is required because of the economic, manufacturing or assembly

For aerodynamic and conjugate heat transfer problems, the work reported in this article investigated the effect of the grid displacement model on the derivatives of an objective function with respect to the design variables. A comparison was made in the first step of the study between reference sensitivity derivatives computed by finite differences and different grid displacement models (volumetric