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14 pages, 1203 KiB

Open AccessArticle

Multi-Objective Bus Timetable Coordination Considering Travel Time Uncertainty

by Xueping Dou and Tongfei Li

Processes 2023, 11(2), 574; https://doi.org/10.3390/pr11020574 - 13 Feb 2023

Cited by 3 | Viewed by 1334

Abstract

This paper proposes a timetable coordination method for transfer problems in a bus transit system. With a given bus network, a stochastic mixed-integer linear programming (MILP) model has been formulated to obtain coordinated bus timetables with the objective of minimizing a weighted sum [...] Read more.

This paper proposes a timetable coordination method for transfer problems in a bus transit system. With a given bus network, a stochastic mixed-integer linear programming (MILP) model has been formulated to obtain coordinated bus timetables with the objective of minimizing a weighted sum of the average value of total waiting time and its average absolute deviation value, allowing for random bus travel time. The vital decision variable is the terminal departure offset time of each target bus trip within a certain off-peak period. The robust MILP model can also be used to solve the first-bus transfer problem with the introduction of several new linear constraints. A solution method based on the Monte Carlo simulation has been developed to solve the MILP model. Numerical experiments have been conducted for different scenarios. The results indicate that bus timetables coordinated by the developed model are capable of substantially reducing waiting time for transfer and non-transfer passengers. In addition, the feasibility of simplifying a common sub-route into a single transfer stop in a timetable coordination problem has been explored based on numerical experiments. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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20 pages, 5885 KiB

Open AccessArticle

Mapping the Shifting Focus in Remote Sensing Literature: Technology, Methodology, and Applications

by Xintao Li, Shuhan Li, Minxiao Zhao, Xin Guo and Tingjun Zhang

Processes 2023, 11(2), 571; https://doi.org/10.3390/pr11020571 - 13 Feb 2023

Cited by 1 | Viewed by 2735

Abstract

This paper characterizes the body of knowledge on remote sensing from 1999 to 2021 by employing bibliometric techniques based on the Science Citation Index databases and the Social Science Citation Index of the Web of Science, abbreviated to “SCI” and “SSCI”, respectively. A [...] Read more.

This paper characterizes the body of knowledge on remote sensing from 1999 to 2021 by employing bibliometric techniques based on the Science Citation Index databases and the Social Science Citation Index of the Web of Science, abbreviated to “SCI” and “SSCI”, respectively. A total of 28,438 articles were analyzed from various aspects of the publication characteristics, such as countries, institutes, subjects, journals, and keywords. Dynamic changes in published remote sensing research were examined by segregating the 19-year period into 4 stages. Co-occurrences of keywords from three aspects were evaluated, including technology, methodology, and applications. Results show that “hyperspectral remote sensing”, “classification”, “monitoring” and “MODIS” in the category of technology have emerged more frequently in recent years, and there are strong co-occurrences of “remote sensing” and “GIS” in the remote sensing technology category. In addition, there was a marked shift from traditional analytical methods (i.e., geostatistics and neural networks) to a variety of emerging methods, such as support vector machines, random forests, and feature extraction. Moreover, research hotspots are identified for remote sensing applications, which have expanded significantly with improvements in technology and methodology. In particular, “water quality”, “climate change”, and “urbanization” have become popular themes in recent years. Finally, future directions of remote sensing are identified, which would be beneficial for researchers and policy makers. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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14 pages, 1371 KiB

Open AccessArticle

Solving Tea Blending Problems Using Interactive Fuzzy Multi-Objective Linear Programming

by Saran Jarernsuk and Busaba Phruksaphanrat

Processes 2023, 11(1), 49; https://doi.org/10.3390/pr11010049 - 26 Dec 2022

Cited by 2 | Viewed by 2519

Abstract

Blending is a classical and well-known optimization problem that has been applied in the food, steel, and composite material industries. However, tea blending is more complicated than general problems due to the variety of products, processes, and sources of raw materials and semi-products. [...] Read more.

Blending is a classical and well-known optimization problem that has been applied in the food, steel, and composite material industries. However, tea blending is more complicated than general problems due to the variety of products, processes, and sources of raw materials and semi-products. So, in this research, a fuzzy multi-objective model for the tea blending problem was proposed to minimize the total production cost and the deviation of quality target score; it provides a more robust and flexible method than existing models for complex real-world problems. Existing research works of a blending problem consider only raw material cost, but semi-product cost and processing cost are included in the proposed model that matches the actual case. Losses that occur during production are also incorporated. The selection of appropriate raw materials and semi-product sources can be obtained with the preferred levels of cost and quality by the proposed algorithm. The interactive fuzzy multi-objective programming to solve the problem has advantages over existing interactive programming methods. It is easy to manipulate interactively to obtain more efficient solutions than existing methods and both balanced and unbalanced solutions can be selected. The comparison of the results of an existing approach and the interactive fuzzy multi-objective programming algorithm for the tea industry is illustrated. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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27 pages, 3804 KiB

Open AccessArticle

Unforgeable Digital Signature Integrated into Lightweight Encryption Based on Effective ECDH for Cybersecurity Mechanism in Internet of Things

by Adel A. Ahmed and Omar M. Barukab

Processes 2022, 10(12), 2631; https://doi.org/10.3390/pr10122631 - 7 Dec 2022

Cited by 3 | Viewed by 1798

Abstract

Cybersecurity protocols enable several levels of protection against cyberattacks (digital attacks) that spread across network devices, platform programs, and network applications. On the Internet of Things (IoT), cyberattacks are generally intended to access and change/destroy sensitive information, which may reduce IoT benefits. Moreover, [...] Read more.

Cybersecurity protocols enable several levels of protection against cyberattacks (digital attacks) that spread across network devices, platform programs, and network applications. On the Internet of Things (IoT), cyberattacks are generally intended to access and change/destroy sensitive information, which may reduce IoT benefits. Moreover, recent IoT systems are experiencing a critical challenge in designing a lightweight and robust cybersecurity mechanism on resource-constrained IoT devices. The cybersecurity challenges facing the IoT that should be taken into consideration are identifying compromised devices, data/service protection, and identifying impacted IoT users. This paper proposes an unforgeable digital signature integrated into an effective lightweight encryption (ELCD) mechanism that utilizes the secure key distribution in an elliptic curve Diffie–Hellman (ECDH) and resolves the weak bit problem in the shared secret key due to the Diffie–Hellman exchange. The ELCD mechanism proposes a secure combination between the digital signature and encryption, and it uses fast hash functions to confidentially transfer a shared secret key among IoT devices over an insecure communication channel. Furthermore, the ELCD mechanism checks the true identity of the sender with certainty through the proposed digital signature, which works based on a hash function and three steps of curve-point inspection. Furthermore, the security of ELCD was mathematically proven using the random oracle and IoT adversary models. The findings of the emulation results show the effectiveness of ELCD in terms of CPU execution time, storage cost, and power consumption that are less by 53.8%, 33–17%, and 68.7%, respectively, compared to the baseline cryptographic algorithms. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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22 pages, 1241 KiB

Open AccessArticle

Policy Evaluation and Policy Style Analysis of Ride-Hailing in China from the Perspective of Policy Instruments: The Introduction of a TOE Three-Dimensional Framework

by Xintao Li, Shuochen Zhang, Diyi Liu, Tongshun Cheng and Zaisheng Zhang

Processes 2022, 10(10), 2035; https://doi.org/10.3390/pr10102035 - 8 Oct 2022

Cited by 2 | Viewed by 2571

Abstract

Online ride-hailing in China brings convenience for the public, but it has caused several problems, such as inadequate supervision, data security risks, and financial risks. This new industry has also disrupted the traditional taxi market. China’s government implemented some policies, which were initially [...] Read more.

Online ride-hailing in China brings convenience for the public, but it has caused several problems, such as inadequate supervision, data security risks, and financial risks. This new industry has also disrupted the traditional taxi market. China’s government implemented some policies, which were initially disorderly tightening, and then formed the policy system responding to various needs for tackling these issues gradually. There were some policy fluctuations and regulatory effects during this period, therefore, it is imminent to evaluate the online ride-hailing policy text. In this paper, we took 43 online ride-hailing policies as samples, with the consideration of policy instruments and statistical inspection methods. In this paper, we also constructed an innovative three-dimensional analysis framework by combining content analysis, and further identify the ride-hailing policy development during different stages of development periods (2016–2022). Digging into the problems existing in the new online ride-hailing, policies were drawn by module division, unit coding, inductive statistics, the quantitative evaluation of policy text content, and TOE (technology-organization-environment) style analysis. Finally, we provide insightful policy recommendations for online ride-hailing policies, committed to providing theoretical support and a decision-making basis for governance policies in the transportation industry. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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23 pages, 565 KiB

Open AccessArticle

Hybrid Memetic Algorithm to Solve Multiobjective Distributed Fuzzy Flexible Job Shop Scheduling Problem with Transfer

by Jinfeng Yang and Hua Xu

Processes 2022, 10(8), 1517; https://doi.org/10.3390/pr10081517 - 1 Aug 2022

Cited by 6 | Viewed by 1700

Abstract

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 uncertain. Therefore, we consider the uncertainty of processing [...] Read more.

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 uncertain. Therefore, we consider the uncertainty of processing environment, and for the first time propose a multiobjective distributed fuzzy flexible job shop scheduling problem with transfer (MO-DFFJSPT). To solve the MO-DFFJSPT, a hybrid decomposition variable neighborhood memetic algorithm (HDVMA) is proposed with the objectives of minimizing the makespan, maximum factory load, and total workload. In the proposed HDVMA, the well-designed encoding/decoding method and four initialization rules are used to generate the initial population, and several effective evolutionary operators are designed to update populations. Additionally, a weight vector is introduced to design high quality individual selection rules and acceptance criteria. Then, three excellent local search operators are designed for variable neighborhood search (VNS) to enhance its exploitation capability. Finally, a Taguchi experiment is designed to adjust the important parameters. Fifteen benchmarks are constructed, and the HDVMA is compared with four other famous algorithms on three metrics. The experimental results show that HDVMA is superior to the other four algorithms in terms of convergence and uniformity of non-dominated solution set distribution. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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25 pages, 3378 KiB

Open AccessArticle

Multiobjective Optimization Based on “Distance-to-Target” Approach of Membrane Units for Separation of CO₂/CH₄

by Ricardo Abejón, Clara Casado-Coterillo and Aurora Garea

Processes 2021, 9(11), 1871; https://doi.org/10.3390/pr9111871 - 21 Oct 2021

Cited by 9 | Viewed by 1503

Abstract

The effective separation of CO₂ and CH₄ mixtures is essential for many applications, such as biogas upgrading, natural gas sweetening or enhanced oil recovery. Membrane separations can contribute greatly in these tasks, and innovative membrane materials are being developed for this [...] Read more.

The effective separation of CO₂ and CH₄ mixtures is essential for many applications, such as biogas upgrading, natural gas sweetening or enhanced oil recovery. Membrane separations can contribute greatly in these tasks, and innovative membrane materials are being developed for this gas separation. The aim of this work is the evaluation of the potential of two types of highly CO₂-permeable membranes (modified commercial polydimethylsiloxane and non-commercial ionic liquid–chitosan composite membranes) whose selective layers possess different hydrophobic and hydrophilic characteristics for the separation of CO₂/CH₄ mixtures. The study of the technical performance of the selected membranes can provide a better understanding of their potentiality. The optimization of the performance of hollow fiber modules for both types of membranes was carried out by a “distance-to-target” approach that considered multiple objectives related to the purities and recovery of both gases. The results demonstrated that the ionic liquid–chitosan composite membranes improved the performance of other innovative membranes, with purity and recovery percentage values of 86 and 95%, respectively, for CO₂ in the permeate stream, and 97 and 92% for CH₄ in the retentate stream. The developed multiobjective optimization allowed for the determination of the optimal process design and performance parameters, such as the membrane area, pressure ratio and stage cut required to achieve maximum values for component separation in terms of purity and recovery. Since the purities and recoveries obtained were not enough to fulfill the requirements imposed on CO₂ and CH₄ streams to be directly valorized, the design of more complex multi-stage separation systems was also proposed by the application of this optimization methodology, which is considered as a useful tool to advance the implementation of the membrane separation processes. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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Review

Jump to: Research

15 pages, 2997 KiB

Open AccessFeature PaperReview

Applications of Multi-Objective Optimization to Industrial Processes: A Literature Review

by Sandra C. Cerda-Flores, Arturo A. Rojas-Punzo and Fabricio Nápoles-Rivera

Processes 2022, 10(1), 133; https://doi.org/10.3390/pr10010133 - 10 Jan 2022

Cited by 15 | Viewed by 4879

Abstract

Industrial processes provide several of the products and services required for society. However, each industry faces different challenges from different perspectives, all of which must be reconciled to obtain profitable, productive, controllable, safe and sustainable processes. In this context, multi-objective optimization has become [...] Read more.

Industrial processes provide several of the products and services required for society. However, each industry faces different challenges from different perspectives, all of which must be reconciled to obtain profitable, productive, controllable, safe and sustainable processes. In this context, multi-objective optimization has become a powerful tool to aid the decision-making mechanism in the synthesis, design, operation and control of such processes. The solution to the mathematical models provides the necessary tools to asses the system performance in terms of different metrics and evaluate the trade-offs between the objectives in conflict. The number of applications of multi- objective optimization in industrial processes is ample and each application has its own challenges. In the present literature review, a broad panorama of the applications in multi-objective optimization is presented, including future perspectives and open questions that still need to be addressed. Full article

(This article belongs to the Special Issue Multi-Objective Optimization of Industrial Processes)

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