In this paper, an improved hybridization of an evolutionary algorithm, named permutated oppositional differential evolution sine cosine algorithm (PODESCA) and also a sensitivity-based decision-making technique (SBDMT) are proposed to tackle the opti...
This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutio...
In recent years, technologies for renewable energy utilization have been booming. Hybrid renewable energy systems (HRESs), integrating multiple energy sources to mitigate the unstable, unpredictable, and intermittent characteristics of a single renew...
Multi-robot task allocation (MRTA) and route planning are crucial for a large-scale multi-robot system. In this paper, the problem is formulated to minimize the total energy consumption and overall task completion time simultaneously, with some const...
Optimization is a process of minimizing or maximizing a given objective function under specified constraints. In multi-objective optimization (MOO), multiple conflicting functions are optimized within defined criteria. Numerous MOO techniques have be...
Representing and analyzing the complexity of models constructed by data is a difficult and challenging task, hence the need for new, more effective techniques emerges, despite the numerous methodologies recently proposed in this field. In the present...
Ship collisions cause major losses in terms of property, equipment, and human lives. Therefore, more investigations should be focused on this problem, which mainly results from human error during ship control. Indeed, to reduce human error and consid...
A common technique used to solve multi-objective optimization problems consists of first generating the set of all Pareto-optimal solutions and then ranking and/or choosing the most interesting solution for a human decision maker (DM). Sometimes this...
The decrease in employee performance that occurs during organizational change is one of the main problems that this study attempts to address. This phenomenon, which is known as resistance to change, has been directly linked to the failure or abandon...
28 March 2018
The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which inclu...
Objectives: The purpose of this study was to assess the feasibility of the adoption of a machine learning (ML) algorithm in support of the investment decisions regarding high cost medical devices based on available clinical and epidemiological eviden...
Urban traffic congestion is a pressing issue, demanding effective and cost-efficient solutions. This paper develops the Traffic Weighted Multi-Maps (TWM) method to solve the Traffic Assignment Problem in Intelligent Transportation Systems (ITS). TWM...
As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Al...
High Performance Computing Clusters (HPCCs) are common platforms for solving both up-to-date challenges and high-dimensional problems faced by IT service providers. Nonetheless, the use of HPCCs carries a substantial and growing economic and environm...
Companies are constantly changing in their organization and the way they treat information. In this sense, relevant data analysis processes arise for decision makers. Similarly, to perform decision-making analyses, multi-criteria and metaheuristic me...
Hybrid Evolutionary–Fuzzy Systems (HEFS) have emerged as a powerful computational paradigm for addressing complex engineering optimization and intelligent decision-making problems under uncertainty. This study presents a systematic review, cond...
This paper aims to study the problems of surplus interaction, poor real-time performance, and excessive processing of information in the micro-grid scheduling and decision-making process. Firstly, the micro-grid dual-loop mobile topology structure is...
This paper presents a two-step approach for optimizing the configuration of a mobile photovoltaic-diesel-storage microgrid system. Initially, we developed a planning configuration model to ensure a balance between the mobility of components and a sus...
Competitive optimization techniques have been developed to address the complexity of integrated water resources management (IWRM) modelling; however, model adaptation due to changing environments is still a challenge. In this paper we employ multi-va...
This paper proposes a dynamic membrane algorithm (DMA)-oriented computing framework designed to optimize decision-making in Customer-to-Green-Manufacturer (C2GM) operations on industrial internet platforms. Unlike traditional methods that focus solel...
In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policymakers and renewable energy experts working on...
With the rapid advancement of digitalization, data-intensive computing, and artificial intelligence (AI), multi-objective optimization (MOO) has shifted from traditional mathematical modeling and algorithmic solving toward integrated decision-support...
The development of the new energy vehicle (NEV) industry has become a key driver of the global low-carbon transition. Understanding the policy effect on NEV diffusion is essential to promote sustainable growth. In this study, we propose a new approac...
Human capital management is a strategic element for companies in a globalized world. Therefore, they must use strategies and methods to recruit and select personnel assertively to focus their training, strengthening, and business growth efforts. Pers...
The advancement toward sustainable infrastructure presents complex multi-objective optimization (MOO) challenges. This paper expands the current understanding of design frameworks that balance cost, environmental impacts, social factors, and structur...
Human beings have created numerous laws, sayings and proverbs that still influence behaviors and decision-making processes of people. Some of the laws, sayings or proverbs are used by people to understand the phenomena that may take place in daily li...
The unplanned development of agricultural land and urban areas poses threats to water quality, which can lead to the death of the aquatic species in rivers. The present study developed a novel framework by combining a soil and water assessment tool (...
Most of the practical applications that require optimization often involve multiple objectives. These objectives, when conflicting in nature, pose both optimization as well as decision-making challenges. An optimization procedure for such a multi-obj...
Unmanned aerial vehicle (UAV) swarm dynamic combat poses significant challenges due to its complexity and dynamism. This study introduces a novel approach that addresses these challenges through the development of a swarm maneuver decision method bas...
The cherry fruit fly (Rhagoletis cerasi L.) poses a major threat to global cherry production, with significant economic implications. This study presents an innovative approach to assist pest control strategies by classifying cherry fruit samples bas...
To address the dynamic decision-making and control problem in unmanned aerial vehicle (UAV) swarms, this paper proposes a cumulative prospect theory-driven pigeon-inspired optimization (CPT-PIO) algorithm. Gray relational analysis and information ent...
Port and shipping enterprises face significant uncertainty in making effective sustainable investment decisions to meet pressing carbon reduction targets. This study addresses this challenge by developing a fuzzy multi-method framework to identify an...
Multi-agent decision-making faces many challenges such as non-stationarity and sparse rewards, while the complexity and randomness of the real environment further complicate policy development. This paper addresses the high-dimensional policy optimiz...
Countless endeavors have been undertaken to address the Byzantine Generals Problem, a generalization of the Two Generals Problem. The emergence of proof of work (PoW) for Bitcoin has led to various consensus algorithms diverging, and comparable exist...
Aspects concerning resonance and global stability of a wind turbine blade must be carefully considered in its optimal design. In this paper, a composite wind turbine blade with an external geometry based on the NREL 5 MW model was subjected to multi-...
This study applies deep learning predictive networks and multi-objective decision-making algorithms to the context of innovation and entrepreneurship education, aiming to explore the characteristics of students in different majors regarding innovatio...
Multi-objective optimization problems (MOPs) are ubiquitous in scientific research and engineering applications, where multiple conflicting objectives must be optimized simultaneously. Unlike traditional multi-objective evolutionary algorithms, which...
As the number of feature dimensions increases, the decision-making space exhibits extensive and discrete characteristics, which poses a severe challenge to multi-objective (MO) evolutionary algorithms when searching for the optimal feature subset. Ma...
Background: Preeclampsia remains a leading cause of maternal morbidity worldwide. There is a critical need for predictive systems that not only perform accurately but also provide interpretable insights for clinical decision-making. This work introdu...
In many areas, such as mobile robots, video games and driverless vehicles, path planning has always attracted researchers’ attention. In the field of mobile robotics, the path planning problem is to plan one or more viable paths to the target l...
The decision-making of sustainable supply chain network (SSCN) design is a strategy capacity for configuring network facility and product flow. When optimizing conflicting economic, environmental, and social performance objectives, it is difficult to...
As global energy systems transition towards greater reliance on renewable energy sources, the integration of energy storage systems (ESSs) becomes increasingly critical to managing the intermittency and variability associated with renewable generatio...
A robust decision-making tool is needed to meet sustainability challenges and to manage water resources that are under development pressure, water scarcity, and climate change impact. To tackle such challenges, optimization modelling can be employed...
With the continuous increase in highway mileage and vehicles in China, highway accidents are also increasing year by year. However, the on-site disposal procedures of highway accidents are complex, which makes it difficult for the emergency departmen...
Multi-objective evolutionary algorithms (MOEAs) are widely used to optimize multi-purpose reservoir operations. Considering that most outcomes of MOEAs are Pareto optimal sets with a large number of incomparable solutions, it is not a trivial task fo...
This study explores the integrated scheduling optimization of coal port operations, addressing the dual challenges of handling efficiency and resource conservation by coordinating equipment scheduling with stockyard spraying operations. Through a sys...
24 October 2024
Study Design: This study presents a review of the evolutionary development in reconstructive orbital surgery over the past 3 decades. Additionally, it proposes the Orbital Assessment Algorithm (OA2) to enhance decision-making for intraorbital reconst...
The rapid evolution of intelligent cluster systems—such as UAV swarms and networked autonomous agents—has brought spatial optimization and decision-making to the forefront of intelligent systems research. This paper provides a systematic...
Shading system design is a complex, multi-objective optimization problem that requires balancing interdependent economic, environmental, social, energy, architectural, and daylighting factors, while also integrating decision-makers’ preferences...
We propose a hybrid intelligent methodology for forecasting outcomes in complex human-centered systems characterized by uncertainty and reliance on expert knowledge. The framework integrates fuzzy cognitive maps (FCMs), a novel Least-Influence Method...
of 5