Given a graph G with n vertices and l edges, the load distribution of a coloring q: V → {red, blue} is defined as dq = (rq, bq), in which rq is the number of edges with at least one end-vertex colored red and bq is the number of edges with at le...
This study aims to compare the results of a memetic algorithm with those of the two-phase decomposition heuristic on the external depot production routing problem in a supply chain. We have modified the classical scheme of a genetic algorithm by repl...
Local Positioning Systems (LPS) have shown excellent performance for applications that demand high accuracy. They rely on ad-hoc node deployments which fit the environment characteristics in order to reduce the system uncertainties. The obtainment of...
In this paper, we present a novel memetic algorithm (MA) for the solution of the resource leveling problem (RLP). The evolutionary framework of the MA is based on integration of a genetic algorithm and simulated annealing methods along with a resourc...
Flow-shop scheduling problems are classic examples of multi-resource and multi-operation scheduling problems where the objective is to minimize the makespan. Because of the high complexity and intractability of the problem, apart from some exceptiona...
We propose a memetic algorithm for the multiple-choice multidimensional knapsack problem (MMKP). In this study, we focus on finding good solutions for the MMKP instances, for which feasible solutions rarely exist. To find good feasible solutions, we...
The green vehicle routing problem is a variation of the classic vehicle routing problem in which the transportation fleet is composed of electric vehicles with limited autonomy in need of recharge during their duties. As an NP-hard problem, this prob...
This paper presents a memetic algorithm (MA) for energy cost estimation of a robot path. The developed algorithm uses a random recombination genetic algorithm (GA) as the basis for the first stage of the algorithm and performs a local search based on...
The vehicle-routing problem (VRP) has many variants, including the most accurate models of real-life transportation tasks, making it one of the most important mathematical problems in the field of logistics. Our goal was to design an algorithm that c...
This paper deals with the flow shop scheduling problem. To find the optimal solution is an NP-hard problem. The paper reviews some algorithms from the literature and applies a benchmark dataset to evaluate their efficiency. In this research work, the...
In this paper, a novel modified auto disturbance rejection control (ADRC) design of a permanent magnet synchronous motor based on the improved memetic algorithm (IMA) is proposed. Firstly, there is an obvious system ripple caused by the defect that t...
Node localization, which is formulated as an unconstrained NP-hard optimization problem, is considered as one of the most significant issues of wireless sensor networks (WSNs). Recently, many swarm intelligent algorithms (SIAs) were applied to solve...
Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MO...
Hostelry establishments face the challenge of devising a table and chair allocation for accommodating their customers on a daily basis. This problem scales significantly with the introduction of constraints, such as scenario obstacles or the requirem...
Distributed scheduling has become a common manufacturing mode, and the distributed job scheduling problem (DJSP) has attracted more manufacturers and researchers in the field of operation research. For the distributed scheduling problem, it emphasize...
The quadratic minimum spanning tree problem (QMSTP) is a spanning tree optimization problem that considers the interaction cost between pairs of edges arising from a number of practical scenarios. This problem is NP-hard, and therefore there is not a...
Reclaiming–loading operations in dry bulk terminals often face conflicts and delays due to limitations in equipment processing capacity and operational line accessibility, which significantly compromise the safety and efficiency of these operat...
Recognized as an NP-hard combinatorial challenge, Storage Location Assignment Problem (SLAP) demands heuristic or algorithmic solutions for effective optimization. This paper specifically examines the enhancement of SLAP through the utilization of ev...
Due to the high power bills and the negative environmental impacts, workflow scheduling with energy consciousness has been an emerging need for modern heterogeneous computing systems. A number of approaches have been developed to find suboptimal sche...
The automotive suspension must perform competently to support comfort and safety when driving. Traditionally, car suspension control tuning is performed through trial and error or with classical techniques that cannot guarantee optimal performance un...
Selecting the minimal best subset out of a huge number of factors for influencing the response is a fundamental and very challenging NP-hard problem because the presence of many redundant genes results in over-fitting easily while missing an importan...
Encouraging healthy and balanced diet plans is one of the most important action points for governments around the world. Generating healthy, balanced and inexpensive menu plans that fulfil all the recommendations given by nutritionists is a complex a...
Hybrid electric vehicle (HEV) control strategy is a management approach for generating, using, and saving energy. Therefore, the optimal control strategy is the sticking point to effectively manage hybrid electric vehicles. In order to realize the op...
Many transport systems in the real world can be modeled as networked systems. Due to limited resources, only a few nodes can be selected as seeds in the system, whose role is to spread required information or control signals as widely as possible. Th...
Variable machine efficiency (VME) and maintenance activities (MA) are critical factors often unexplored in job scheduling problems. This paper introduces a new problem termed the job-shop scheduling problem with variable machine efficiency and mainte...
Accurate localization is a critical task in underwater navigation. Typical localization methods use a set of acoustic sensors and beacons to estimate relative position, whose geometric configuration has a significant impact on the localization accura...
Unmanned aerial vehicles (UAVs) are one of the devices used to collect big data as part of the artificial intelligence of things (AIoT). To reduce total energy consumption, most researchers focus on optimizing the number and the location of UAVs, but...
Most studies on distributed flexible job shop scheduling problem (DFJSP) assume that both processing time and transmission time are crisp values. However, due to the complexity of the factory processing environment, the processing information is unce...
The quality of the initial population is a critical factor in the convergence speed and overall performance of an optimization algorithm. A well-structured initial population can significantly enhance the exploration capabilities of the algorithm, al...
Voltage source converter (VSC) has been extensively applied in renewable energy systems which can rapidly regulate the active and reactive power. This paper aims at developing a novel optimal nonlinear adaptive control (ONAC) scheme to control VSC in...
Most multi-objective studies on distributed hybrid flow shops that include tardiness-related objectives focus solely on optimizing makespan alongside a single tardiness objective. However, in real-world scenarios with strict contractual deadlines or...
Deployment of wireless sensor networks (WSNs) has drawn much attention in recent years. Given the limited energy for sensor nodes, it is critical to implement WSNs with energy efficiency designs. Sensing coverage in networks, on the other hand, may d...
This paper addresses the problem of scheduling a set of jobs on a machine with time-varying capacity, with the goal of minimizing the total tardiness objective function. This problem arose in the context scheduling the charging times of a fleet of el...
Kernel partial least squares regression (KPLS) is a non-linear method for predicting one or more dependent variables from a set of predictors, which transforms the original datasets into a feature space where it is possible to generate a linear model...
Local Positioning Systems rely on ad-hoc node deployments which fit the environment characteristics in order to reduce system uncertainties. The obtainment of competitive results through these systems requires the solution of the Node Location Proble...
The COVID-19 pandemic has challenged all physical interactions. Social distancing, face masks and other rules have reshaped our way of living during the last year. The impact of these measures for indoor establishments, such as education or hostelry...
A new radial memetic algorithm is proposed to resolve the no-wait job-shop scheduling problem. Basically, each sequencing solution is factorized as a distance-based ranking model, i.e., each solution is decomposed in n − 1 terms, where n is the...
The orthogonality of transmitted waveforms is an important factor affecting the performance of MIMO radar systems. The orthogonal coded signal is a commonly adopted waveform in MIMO radar, and its orthogonality depends on the used orthogonal discrete...
The minimum weight vertex independent dominating set (MWVIDS) problem is an important version of the minimum independent dominating set. The MWVIDS problem has a number of applications in many fields. However, the MWVIDS problem is known to be NP-har...
This research is focused on evolutionary algorithms, with genetic and memetic algorithms discussed in more detail. A graph theory problem related to finding a minimal Hamiltonian cycle in a complete undirected graph (Travelling Salesman Problem&mdash...
This paper studies the Cumulative Capacitated Vehicle Routing Problem, including Priority Indexes, a variant of the classical Capacitated Vehicle Routing Problem, which serves the customers according to a certain level of preference. This problem can...
In the last 30 years, a flexible job shop scheduling problem (FJSP) has been extensively explored. Production efficiency is a widely utilized objective. With the rise in environmental awareness, green objectives (e.g., energy consumption) have receiv...
The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of t...
The paper presents a new memetic, cluster-based methodology for image registration in case of geometric perturbation model involving translation, rotation and scaling. The methodology consists of two stages. First, using the sets of the object pixels...
The paper presents a memetic modification of the classical genetic algorithm by introducing a cyclic symmetrization of the population, symmetrizing the parental points around the current population leader. Such an operator provides a more spherical d...
This article presents the author’s own metaheuristic cryptanalytic attack based on the use of differential cryptanalysis (DC) methods and memetic algorithms (MA) that improve the local search process through simulated annealing (SA). The sugges...
Many technological applications of our time rely on images captured by multiple cameras. Such applications include the detection and recognition of objects in captured images, the tracking of objects and analysis of their motion, and the detection of...
Flu vaccine allocation is of great importance for safeguarding public health and mitigating the impact of influenza outbreaks. In this regard, decision-makers face multifaceted challenges, including limited vaccine supply, targeting vulnerable people...
Coverage maintenance is a bottleneck restricting the development of underwater acoustic sensor networks (UASNs). Since the energy of the nodes is limited, the coverage of UASNs may gradually decrease as the network operates. Thus, energy-saving cover...
Structural balance in fully signed networks, integrating both individual attributes and relationships, represents a critical challenge in social computing; however, its dynamic transformation remains underexplored. This study extends structural balan...
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