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A bi-objective function optimization approach for multiple sequence alignment using genetic algorithm

SOFT COMPUTING 2020年第20期24卷 15871-15888页

作者： Chowdhury, biswanath Garai, Gautam Univ Calcutta Dept Biophys Mol Biol & Bioinformat Kolkata India Saha Inst Nucl Phys Comp Sect Kolkata India

Multiple sequence alignment (MSA) is characterized as a very high computational complex problem. Therefore, MSA problem cannot be solved by exhaustive methods. Nowadays, MSA is being solved by optimizing more than one objective simultaneously. In this paper, we propose a new genetic algorithm based alignment technique, named bi-objective sequence alignment using genetic algorithm (BSAGA). The novelty of this approach is its selection process. One part of the population is selected based on the Sum of Pair, and rest is selected based on Total Conserve Columns. We applied integer-based chromosomal coding to represent only the gap positions in an alignment. Such representation improves the search technique to reach an optimum even for longer sequences. We tested and compared the alignment score of BSAGA with other relevant alignment techniques on BAliBASE and SABmark. The BSAGA shows better performance than others do, which was further proved by the Wilcoxon sign test.

关键词： Multiple sequence alignment Genetic algorithm Integer coding Selection Wilcoxon sign test Experimental comparison bi-objective function

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A simplified recursive approach to combined economic emission dispatch

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2008年第1期36卷 17-27页

作者： Balamurugan, R. Subramanian, S. Annamalai Univ Dept Elect Engn Annamalainagar 608002 Tamil Nadu India

This article presents a simplified mathematical approach to find the optimal solution for combined economic and emission dispatch (CEED) problem. In this article, a CEED problem is formulated as a multi-objective problem by considering both economy and emission simultaneously. The bi-objective CEED problem is converted into single objective function using price penalty factor. A dynamic programming (DP) technique is presented in a simple form to solve the CEED problem. The validity of the proposed approach is tested on two sample systems and the results are compared to those reported in the recent literature. The study results have shown that the approach developed is efficient and suitable for real time applications.

关键词： economic dispatch emission dispatch bi-objective function price penalty factor dynamic programming

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Research on Modeling Method for Optimal Allocation of Wellhead Targets in Large Well Clusters

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PROCESSES 2024年第8期12卷 1705页

作者： Wang, Liupeng Duan, Haonan Liu, Zhikun Peng, Yuanchao Liu, Xuyang Xian Shiyou Univ Coll Petr Engn Xian 710065 Peoples R China Chuanqing Drilling Engn & Technol Res Inst Xian 710021 Peoples R China

The paper proposes a genetic ant colony algorithm that integrates genetic and ant colony algorithms, enhancing the heuristic function of the latter, to address target point distribution issues in large well clusters. This algorithm utilizes genetic algorithms for initial pheromone distribution and employs the ant colony algorithm to achieve rapid convergence. Introducing genetic operators in each iteration addresses the ant colony system's drawbacks, including scarcity of initial pheromones, susceptibility to local optima, and slow convergence speed. The model aims to minimize the sum of horizontal displacement and intersections in line connections from wellheads to target points as its dual-objective function. It validates the effectiveness of the genetic ACO algorithm in optimizing target point allocation at wellheads through a case study, highlighting its advantages over traditional methods in reducing displacement, ensuring result stability, and preventing collisions.

关键词： large well clump wellhead target assignment genetic ant colony algorithm horizontal displacement minimization bi-objective function

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Two bi-objective hybrid approaches for the frequent subgraph mining problem

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APPLIED SOFT COMPUTING 2018年 72卷 291-297页

作者： Farhi, Sidali Hocine Boughaci, Dalila USTHB Elect Engn & Comp Sci Dept El Alia BP 32 Bab Ezzouar Algiers 16111 Algeria

This paper proposes two hybrid bi-objective evolutionary algorithms to solve the frequent subgraph mining problem. In this contribution, we propose to improve the search ability of the stochastic local search (SLS) and the variable neighborhood search (VNS) algorithms by adding genetic operators (crossover and mutation) and Pareto dominance concept. A mined subgraph is defined by a bi-objective function which uses two parameters, support and size. We combine GA and SLS in a hybrid method denoted GASLS and GA with VNS in a hybrid method denoted GAVNS to solve the considered problem. The two proposed methods are implemented and evaluated on two synthetic and five real-world datasets of various sizes and their performance were compared against a single-objective stochastic local search algorithm and the well-known NSGA-II algorithm. The proposed methods are able to discover efficiently diversified subgraphs in the search space by exploring new solutions. The numerical results show that in general the GASLS method provides competitive results and finds high quality solutions compared to the other considered algorithms. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Graph mining Subgraph mining Frequent subgraph Stochastic local search Variable neighborhood search Genetic algorithm Hybrid methods bi-objective function Pareto optimality

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Fuzzy dynamic risk-based maintenance investment optimization for offshore process facilities

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JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES 2019年 57卷 194-207页

作者： Yazdi, Mohammad Nedjati, Arman Abbassi, Rouzbeh Univ Lisbon Inst Super Tecn Ctr Marine Technol & Ocean Engn CENTEC P-1049001 Lisbon Portugal Quchan Univ Technol Ind Engn Dept Quchan Iran Macquarie Univ Fac Sci & Engn Sch Engn Sydney NSW Australia

A methodology for maintenance planning is developed which helps in improving the reliability of the components and safety performance in process facilities. This methodology helps design an optimum safety maintenance investment plan by integrating the optimization techniques and a fuzzy dynamic risk-based method. Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) is applied to deal with uncertain data. The proposed approach employs multi-experts' knowledge which helps to optimize the maintenance investments. A separator system in an offshore process facility platform is selected as a case study to demonstrate the application of the proposed methodology. A practical example in the separator system is surveyed and potential failures and Basic Events (BEs) are identified. Finally, a risk-based maintenance plan is provided for future safety investment analysis. The results indicate that the developed methodology estimates the risk more accurately, which enhances the reliability of future process operations.

关键词： Safety investment Crude oil release Uncertainty bi-objective function Risk analysis

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Design of a reliable bi-objective relief routing network in the earthquake response phase 12th

Design of a reliable bi-objective relief routing network in ...

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12th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS)

作者： Tavakkoli-Moghaddam, Reza Shishegar, Shadab Siadat, Ali Mohammadi, Mehrdad Univ Tehran Coll Engn Sch Ind Engn Tehran *** Iran Arts & Metier ParisTech LCFC 4 Rue Augustin Fresnel F-57070 Metz France Ecole Mines St Etienne Dept Mfg Sci & Logist 880 Route Mimet F-13120 Gardanne France

One of the most critical issues in areas which have recently faced natural disasters is transportation of both injured people to medical centers and relief commodities to their desired destinations. In such situation, due to disruptions, some routes may lose all or part of their capacities and not be able to accept as much vehicles as before. Consequently, the relief vehicles face difficulties to follow their itinerary. Such critical circumstance calls for finding reliable solutions. This study develops a new bi-objective, multi-mode and multi-commodity model, in which the reliability is taken into account to help managers in making more reliable decisions. To solve this model, the TH method is used in order to find the equivalent single objective model and this new model is exactly solved by coding in GAMS software. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： Relief routing response phase bi-objective function robust optimization reliability

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Emergency Patient's Arrivals Management Based on IoT and Discrete Simulation Using ARENA 5th

Emergency Patient's Arrivals Management Based on IoT and Dis...

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5th International Symposium on Ubiquitous Networking (UNet)

作者： Karboub, Kaouter Mohamed, Tabaa Moutaouakkil, Fouad Sofiene, Dellagi Dandache, Abbas HASSAN II Univ Res Fdn Dev & Innovat Sci FRDISI Casablanca Morocco HASSAN II Univ Engn Natl & High Sch Elect & Mechan ENSEM Casablanca Morocco EMSI Casablanca Pluridisciplinary Labs Res & Innovat LPRI Casablanca Morocco Lorraine Univ Lab Genie Ind & Prod Metz LGIPM Metz France

ISBN: (纸本)9783030580070;9783030580087

The healthcare ecosystem is now in a state of flux. Social, economic pressures beside demographic changes disrupt the balance of the health facilities. According to the Organization for Cooperation and Economic Development (OECD, 2004), "the last thirty years have been a period of change and of expansion for health systems". Currently, the major problem remains about controlling the ever-increasing health expenditures. Thus, Hospitals are faced with a triple constraint: cost, time and quality. The current ecosystem must simultaneously integrate these constraints in order to offer the best possible service to patient in a minimum time and at the optimal patient's situation. We focus our interest on patients suffering from heart diseases, but still the global approach of the proposed model valid for other contexts. The proposed model is based on an extreme danger situation consisting of heart attacks. In this paper, we aim to establish an embedded connectivity between heart diseases patients and their physicians. Real time monitoring plays an important role to establish that kind of connectivity. In fact, the proposed simulation model is a Dynamic Stochastic Discrete model realized using ARENA software. All the results presented here are based on random data and can be replaced by real time data extracted and preprocessed using IoT sensors recording, and are referenced to a bi-objective function we are going to present in the following sections.

关键词： Healthcare ecosystem Time Quality Heart diseases Embedded connectivity Simulation Emergency department Dynamic Stochastic Discrete Model bi-objective function IoT sensors

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Balancing Staff Finishing Times vs. Minimizing Total Travel Distance in Home Healthcare Scheduling

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APPLIED SCIENCES-BASEL 2024年第16期14卷 7381页

作者： Saksuriya, Payakorn Likasiri, Chulin Chiang Mai Univ Int Coll Digital Innovat Chiang Mai 50200 Thailand Chiang Mai Univ Fac Sci Dept Math Chiang Mai 50200 Thailand

Cost reduction and staff retention are important optimization objectives in home healthcare (HHC) systems. Home healthcare operators need to balance their objectives by optimizing resource use, service delivery and profits. Minimizing total travel distances to control costs is a common routing problem objective while minimizing total finishing time differences is a scheduling objective whose purpose is to enhance staff satisfaction. To optimize routing and scheduling, we propose mixed integer linear programming with a bi-objective function, which is a subset of the vehicle routing problem with time windows (VRPTWs). VRPTWs is a known NP-hard problem, and optimal solutions are very hard to obtain in practice. Metaheuristics offer an alternative solution to this type of problem. Our metaheuristic uses the simulated annealing algorithm and weighted sum approach to convert the problems to single-objective problems and is equipped with operators including swapping, moving, path exchange and ruin and recreate. The results show, firstly, that the algorithm can effectively find the Pareto front, and secondly, that minimizing total finishing time differences to balance the number of jobs per caretaker is an efficient way to tackle HHC scheduling. A statistical test shows that the algorithm can obtain the Pareto front with a lower number of weighted sum problems.

关键词： vehicle routing problem with time windows minimizing total distance minimizing total finishing time differences home healthcare bi-objective function

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Optimization Techniques for Green Layout Design in Manufacturing Industries: A Meta-Heuristic Analysis

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STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING 2022年第11期68卷 683-692页

作者： Sherfudeen, Sheik Sulaiman Athinamilagi, Muthiah Venkataramanujam, Janakiraman Francis Xavier Engn Coll Dept Mech Engn Tirunelveli India PSR Engn Coll Dept Mech Engn Sivakasi India Vaigai Coll Engn Dept Mech Engn Melur India

Many research papers and much legislation has been published in recent years to control or reduce factory pollution. However, only a few articles have discussed pollution from manufacturing facilities, specifically shop floors, even though this a specific single objective problem. In this research framework, a new variant technique of the jelly fish concept adaptive salp swarm optimization (ASSO) with a familiar Lagrangian relaxation model for lowering Total Material Handling Costs (TMHC) and carbon dioxide (CO2) emissions is presented. Using the Mat Lab software and the improved ASSO, the dragon fly optimization (DFO) algorithm technique, experimental simulations of the existing and recognized design of the studied industry were performed. The simulation results were validated and compared to those of other optimization techniques such as ant bee colony (ABC), simulated annealing (SA), and genetic algorithm (GA). It was determined that the proposed methodology, ASSO, was the most efficient, resulting in 40 % reduction compared to ABC, 38 % DFO, 50 % SA, and 40 % GA in the lowest TMHC, as well as an average 20 % reduction of emission rate in green layout design. These techniques could be combined into a hybrid format for further reduction of the emission rate up to 80 %.

关键词： adaptive salp swarm optimization bi-objective function emission evolutionary computation layout design and total handling costs

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Design of a Reliable bi-objective Relief Routing Network in the Earthquake Response Phase

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Procedia Computer Science 2016年 102卷 74-81页

作者： Reza Tavakkoli-Moghaddam Shadab Shishegar Ali Siadat Mehrdad Mohammadi School of Industrial Engineering College of Engineering University of Tehran Tehran 14399-57131 Iran LCFC Arts et Métier ParisTech 4 Rue Augustin Fresnel Metz 57070 France Dep. of Manufacturing Sciences and Logistics Ecole des Mines de Saint-Etienne 880 route de Mimet Gardanne 13120 France

关键词： Relief routing response phase bi-objective function robust optimization reliability

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