Production planning of an open pit mine is defined as determining the extraction sequence of blocks in the final pit limit with the goal of maximizing Net Present Value (NPV) while considering the constraints imposed on the mining system. Mathematical programming models are used to optimize long-term open pit production planning problems. In real mines with several thousands of blocks and several scheduling

A problem of linking vertices (objects) by a connecting tree is studied under the condition that objects appear at different given times. In this case, the target function depends not only on the total length of the connecting tree but also on the times of constructing its fragments. This problem is shown to be NP-complete even when the linking is done without intermediate vertices. In this article

In this study, a hybrid metaheuristic algorithm called Hybrid Tabu Search (HTS) is proposed for the weight optimization of planar steel structures. The effectiveness of HTS lies in improving the initial conditions of a tabu search algorithm with a greedy search algorithm and a swap operator used in the phase of section selection. The effectiveness of the proposed method is tested and validated on three

ABSTRACT A gradient-based method has been developed and programmed to optimize the NH 3 injections of an existing biomass-fired bubbling fluidized bed boiler, the targets being to minimize both the NO and the NH 3 emissions. In this context, the reactive flow inside the boiler is modelled using a custom-built OpenFOAM ® solver, and then the NO and NH 3 species are calculated using a post-processing

This article presents a novel formulation for geometric nonlinear topology optimization problems. In practical engineering, maximum deflection is frequently used to quantify the stiffness of continuum structures, yet not applied generally as the optimization constraint in geometrically nonlinear topology optimization problems. In this study, the maximum nodal displacement is formulated as a sole constraint

In recent years, the two-sided assembly line (TAL) has become popular since it offers several advantages, such as fewer workstations and movement of fewer workers inside the line. TAL assumes that each mated workstation contains two workstations in parallel, and it can process tasks on the left, on the right or on either side. However, in a traditional TAL, only one worker is responsible for completing

Studies have shown that the production and routing problems have an impact on each other, and the integration of these decisions can considerably improve decision making and reduce costs. In this regard, this research studies the effect of outsourcing on a multi-product production routing problem considering environmental impact. In addition to minimizing greenhouse gas emission costs, in this study

In this article, an explicit topology optimization method is proposed for maximizing the overall stiffness of a multi-material continuum structure embedded with multiple variable-size movable holes based on the Moving Morphable Bars (MMB) method. To this end, multiple sets of morphable bars are used to describe the structural topology of multiphase materials, and level-set functions are used to describe

Approaches based on mechanical equilibrium are described for handling cargo stability in the container loading problem. This problem is expressed as an integer programming model and solved with a branch-and-cut algorithm. Cutting planes are added to avoid generating unstable packings. Three grids of points are used to pack items, and then their weakness and advantages, when combined with the cargo

To achieve a lower starting current, lower losses, lower input power, higher efficiency, higher output torque and higher power factor, a multi-goal optimization design for a six-phase copper rotor induction motor (SCRIM) connected with a radial compressor is proposed. The mended grey wolf optimization (MGWO) and Taguchi method with finite element analysis (FEA) are put forward in this design method

Explicit topology optimization based on moving morphable components (MMCs) is a novel and revolutionary topology optimization framework that may be exploited for the generation of strut-and-tie models (STMs) in concrete structures. The article deals with the generation of STMs by solving a compliance minimization problem subject to a volume constraint. The feasible STMs are generated by a set of components

Particle swarm optimization (PSO) is a representative swarm intelligence algorithm, which has the drawback of being restricted by premature convergence. To make PSO less likely to be restricted by premature convergence and to enhance its exploration and exploitation ability, this article proposes a social spider inspired particle swarm optimization (SSI-PSO). Based on PSO, the proposed algorithm divides

Machining level and manufacturing accuracy have an important influence on the reliability of turbomachinery flow physics and dynamic performance. This article proposes a hybrid uncertainty analysis method for fluid dynamics problems with manufacturing constraints. The parameters with sufficient and insufficient experimental samples are processed by the stochastic method and interval method, respectively

The authors previously analysed a real-world solid waste management (SWM) system using the solid waste optimization life-cycle framework (SWOLF) to identify optimal SWM strategies that meet modelled objectives (e.g. cost, environmental impacts, landfill diversion). While mathematically optimal strategies can support SWM decision making, they may not be readily implementable because of unmodelled objectives

To determine the effects of vehicle components’ size on the optimum structural crashworthiness of a vehicle, sufficient data on the expected crash behaviour are required. Considering the high fiscal cost of obtaining the real crash test data, and extreme computational difficulty associated with relying on high-order numerical models, this work explores the adequacy of a generic two-degree-of-freedom

A coupled-analysis assisted gradient-enhanced kriging (CAGEK) method is introduced to improve the quality and efficiency in solving global multidisciplinary design optimization (MDO) problems when multiple disciplines are coupled and expensive computations are required to evaluate these disciplines. In this method, the multidisciplinary feasible architecture is employed to effectively obtain the values

The main focus in optimization studies, including multi-objective and multi-scenario optimization, is placed on finding the global optimum or global Pareto-optimal solutions, representing the best possible objective values. Manual preferences and selection are required to obtain a single implementable solution from the obtainable Pareto set. For achieving such a single optimum, the multi-scenario property

In the present study, different evolutionary methods, namely the bat algorithm (BA), particle swarm optimization (PSO) and their hybrid (HBP), are employed for the design of trapezoidal open-channel cross-sections with minimum construction cost (concrete lining plus excavation costs). For this purpose, considering open channels with uniform and composite roughness, fixed and variable freeboard, and

This note revisits single machine due-date assignment scheduling with job-dependent learning effects and resource allocation. Under the convex decreasing resource consumption function, the problem is to minimize the scheduling cost subject to a constraint on the total weighted resource consumption cost. Firstly, it is shown that the published results are incorrect by a counter-example from the literature

Variation is the root cause of product quality problems. Variations caused by noise factors often affect the quality of the product during manufacturing, resulting in products that fail to meet customer requirements. In this article, a Bayesian online robust parameter design method is proposed to address the parameter design problem with observable noise factors. The proposed method not only takes

In failure-prone systems, it is important to take into considerations all the failure modes of each component to achieve the optimal system reliability. In this paper, a new series-parallel redundancy allocation problem is presented for a system in which the subsystems and components are subject to two different independent failure modes: short-circuit and open-circuit. It is assumed when a pre-determined

A nonlinear displacement-controlled loading dynamic method is employed to investigate the deformed shape evolution of stiffened shells from prebuckling to postbuckling field until collapse. Because of the time-consuming postbuckling analysis, the dual-elite population sequential approximation optimization (SAO) approach is proposed. A novel determination method of Gaussian kernel widths based on moment

Single-loop methods for reliability-based design optimization are characterized by high computational efficiency. However, the accuracy of these methods may be low for highly nonlinear probabilistic constraints. A new hybrid method called ‘SLShV-CG’ is proposed for improving accuracy in which the single-loop method is coupled with the shifting vector approach of the sequential optimization and reliability

As a kind of production line, the mixed-model assembly line (MMAL) has been progressively adopted by industries to satisfy the diversification of customer demands. This study applied an MMAL sequencing problem for a make-to-order (MTO) strategy. Using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach, this study sorted customer orders, satisfying these by a

This study aims to complement well-established methods based on gradients, such as standard level-set optimization or density-based methods, and extend the field where numerical optimization of structural topologies can be employed. This is, for example, of interest for design problems related to crashworthiness design. Because of the noisy or discontinuous character of the responses, in these cases

In this article, online collaborative content caching in wireless networks is studied from a network economics point of view. The cache optimization problem is first modelled as a finite horizon Markov decision process that incorporates an auto-regressive model to forecast the evolution of the content demands. The complexity of the problem grows exponentially with the system parameters, and even though

This article presents a multi-objective optimal design method for a squeeze film damper (SFD) with centring spring. The proposed method is able to obtain the optimal design parameters for a flexible rotor system. The objectives are minimizing the amplitude of the disk and transmitted force, and maximizing the SFD effectiveness simultaneously. These objectives generally conflict with each other, and

This study examines a two-stage three-machine flow-shop assembly scheduling model in which job processing time is considered as a mixed function of a controlled truncation parameter with a sum-of-processing-times-based learning effect. However, the truncation function is very limited in the two-stage flow-shop assembly scheduling settings. To overcome this limitation, this study investigates a two-stage

Influenced by various random factors, such as a ship's size, arrival time and anchoring spot, the number of ships that can be practically accommodated by the anchorage of a coastal port is generally far lower than the designed anchorage capacity. To address the shortage problem, this article applies a redundancy optimization theory to realize a reasonable and practical design of the anchorage capacity

ABSTRACT Joining sequence optimization is a combinatorial problem, requiring extensive computational time. The significance of determination of an optimal sequence for improved geometrical quality is substantial. Previously, genetic algorithms have been studied for defining the optimal sequence. However, these algorithms are highly dependent on the internal parameters, requiring additional computational

Least squares auto-tuning automatically finds hyper-parameters in least squares problems that minimize another (true) objective. The least squares tuning optimization problem is non-convex, so it cannot be solved efficiently. This article presents a powerful proximal gradient method for least squares auto-tuning that can be used to find good, if not the best, hyper-parameters for least squares problems

In this article, five different formulations for establishing optimal ensembles of metamodels are presented and compared. The comparison is done by minimizing different norms of the residual vector of the leave-one-out cross-validation errors for linear, affine and convex combinations of 10 metamodels. The norms are taken to be the taxicab, the Euclidean and the infinity norm, respectively. The ensemble

In the real world, secondary disasters occur frequently after primary disasters, and their diverse and uncertain nature along with the destruction may make the emergency relief operations more challenging. A scenario-based three-stage stochastic programming model is proposed considering the correlation between primary and secondary disasters under uncertain conditions. In order to enhance the computational

Considerable academic research has been conducted on truss design optimization by standard metaheuristic methods; however, the generic nature of these methods becomes inefficient for problems with many decision variables. This may explain the simplicity of the relevant test problems in the academic literature in comparison with real structures. To address this challenge, this study advocates a customized

A parameter optimization procedure for designing rivet dies is presented to improve the joining quality of an electromagnetic riveted joint. The optimal Latin hypercube sampling technique, radial basis function neural network model and Hooke–Jeeves algorithm were used to construct the optimization model. The results indicated that the rivet die angle was more sensitive to the expansion of the rivet

The optimal design of an accelerated degradation test can effectively shorten the test duration and improve the accuracy of lifetime evaluation. This article proposes a new optimization method that considers the uncertainty of degradation models during the optimal design, and with the application of the combination forecast method based on the Akaike information criterion, establishes the optimization

Eco-driving is one of the most promising methods to reduce the energy consumption of existing railways. Considering the practical situation in complex railway lines, this article proposes a new multi-objective searching algorithm to obtain the set of most efficient speed profiles in train journey for each combination of arrival and intermediate times. This algorithm makes use of the particle swarm

This article investigates the single-machine common due-window assignment problem with generalized earliness/tardiness penalties and a rate-modifying activity. Job processing times include two cases: one with constant values and another with time-dependent processing times (deterioration effect). Considering the maintenance activity, the maintenance time is a fixed constant. The goal is to determine

In the past, several studies have focused on planning for the deployment of charging stations for electric vehicles, with fewer studies being conducted on electric scooters. These works, however, did not consider the characteristics of electric scooters with regard to tourism activities. Therefore, in this study the authors adopt network flow and mathematical programming techniques to develop a model

This article presents Constraint Violation Reduction Search (CVRS), a primal heuristic for 0–1 Mixed Integer Linear Programming (MILP) problems. CVRS constructs a series of MILP subproblems by adding artificial variables representing the amount by which each constraint is violated and minimizing their sum in the objective function. A cutoff constraint added to each subproblem ensures that the objective

Blank holders play an important role in non-isothermal stamping, and blank holder optimization is thus investigated in this article. A kriging-interpolated level-set method based on a parallel infilling strategy is proposed. First, a new method is used to discretize the design domain of a blank holder. The first-stage kriging model between the nodes and level-set values is developed, and a new blank

In open-pit mines, the long-term production scheduling (LTPS) problem is a mixed-integer programming problem and is considered as a class of NP-hard problems that has to be solved in a reasonably small time owing to the operational requirements. The LTPS problem cannot be considered a well-solved problem. The current article presents hybrid models to elucidate the LTPS problem regarding grade uncertainty

This article presents a numerical method based on quantum computing to solve two unresolved key issues for alkali–surfactant–polymer (ASP) flooding in oil exploitation: uncertainties affecting development planning and a switch control regarding injection oil wells. First, a fuzzy multi-objective mixed-integer optimal control model describing the mechanism of ASP flooding is established. Then, an improved

An important challenge in damage detection based on the curvature mode shape (CMS) method is recognizing damage severity in damaged structures. Here, an efficient approach is proposed based on the finite element (FE) method, which detects the existence, location and severity of damage using the distributed genetic algorithm in conjunction with CMS. First, using the mode shape of the structure, curvature

The global fuzzy reliability sensitivity can measure the effect of input on fuzzy failure probability (FFP) through the expected difference between the unconditional FFP and the conditional one. Thus, an efficient method is proposed to estimate this sensitivity index. The proposed method includes two steps. First, the unconditional–conditional FFPs are equivalently transformed into the integrals of

Liquid column vibration absorbers (LCVAs) have been proved to be highly efficient in vibration suppression of buildings under earthquake and wind loads. This article proposes an efficient computational framework for reliability-based optimal design and placement of LCVAs in semi-rigidly connected buildings subjected to stochastic ground motions. The reduced function evaluations method is used as an

This article concerns the optimized planning of the assembly of the top layer of floorboards in the parquet industry. This layer is constructed with lamellas of different lengths and grades that are aligned into three lanes. The grades used and the arrangement of the lamellas define the quality of the floorboard produced. This results in a large number of pattern permutations that must be considered

U-shaped assembly lines have drawn increasing attention from the modern assembly line industry owing to their high flexibility. This work develops an enhanced beam search heuristic algorithm to solve types 1 and 2 U-shaped assembly line balancing problems (UALBP-1 and UALBP-2). The proposed beam search heuristic is enhanced by utilizing: (1) five lower bounds and four dominance rules to prune the dominated

An engineered cluster-based genetic algorithm (ECGA) has been used for performance-based design optimization of two dimensional moment-resisting steel frames (MRSF) considering effects of the soil-structure interaction (SSI). Based on the engineering judgments and via using simple specified filters on defined constrained of the problem, an engineered population is generated. To impose this concept

This article proposes an alternative constraint handling technique for the four-bar linkage path generation problem. The constraint handling technique that is traditionally applied uses an exterior penalty function, and has been found to be inefficient, particularly when dealing with constraints on the input angles. The new technique deals with both input crank rotation and Grashof's criterion. Four

Surrogate models are widely used in engineering design and optimization to substitute computationally expensive simulations for efficient approximation of system behaviours. However, since actual system behaviours are usually not known a priori, it is very challenging to select the most appropriate surrogate model for a specific application. To tackle this, ensemble models that combine different surrogate

This article discusses important improvements in the sensitivity-based coordination method (SCM) for the optimization of product family or quasi-separable problems. In this method, first presented by Zou et al. [Engineering Optimization 48(7), 2016], the system level coordinates each subsystem based on sensitivity information. Test results suggest that the SCM is robust and efficient; however, for

The present article discusses a special variant of the multiphase transportation problem dealing with the transportation of a commodity from various origins to terminals when the set of origin–terminal links is divided into three disjoint partitions, namely Phase-1 links, Phase-2 links and Phase-3 links. Transportation of the commodity via Phase-2 links starts only after the completion of transportation

(2020). Unconventional optimization for achieving well-informed design solutions for the automobile industry. Engineering Optimization: Vol. 52, No. 9, pp. 1542-1560.

Two-stage hybrid flowshop scheduling in a single factory has been considered fully; however, the distributed two-stage hybrid flowshop scheduling problem (DTHFSP) is seldom studied in a multi-factory environment. In this study, a DTHFSP with sequence-dependent setup times is investigated and a shuffled frog-leaping algorithm with memeplex grouping (MGSFLA) is proposed to minimize makespan and the number

In elevating the efficiency and practicality of warehouse operations, our team proposes the concept of interconnected dangerous goods warehouses. To support the operations of this kind of warehouse, this original study addresses three factors that affect the operations of such warehouses, namely the distance traveled by the forklift (cost factors), the similarity between the distances operated by the

In the traditional uncertainty-based analyses and optimizations of the automotive powertrain mounting system (PMS), uncertain parameters are usually treated as either random variables or interval variables. In this article, an efficient analysis and optimization method is proposed for PMS designs with hybrid random and interval uncertainties. An efficient analysis method, named the hybrid perturbation–finite

(2020). Sustainable supplier selection and order allocation: a fuzzy approach. Engineering Optimization: Vol. 52, No. 9, pp. 1494-1507.

Temperature prediction in a slab heating furnace is an important problem for steel production processes. However, the problem is complicated owing to process complexity and industrial noise. These factors make it difficult to obtain precise prediction results by a mechanism model in practical production. In this article, an integrated modelling approach is proposed through combining mechanism and data-driven

Both the distribution and orientation of anisotropic materials have great effects on the performance of civil and mechanical structures. Taking the maximum structural stiffness as the design objective, a concurrent method for determining the optimal distribution and orientation of orthotropic materials is proposed in this article. The method for determining material orientation theoretically overcomes