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A bi-population cooperative scatter search algorithm for distributed hybrid flow shop scheduling with machine breakdown

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 197卷

作者： Zuo, Yang Zhao, Fuqing Zhang, Jianlin Lanzhou Univ Technol Sch Comp & Commun Technol Lanzhou 730050 Peoples R China Henan Inst Technol Elect & Informat Engn Coll Xinxiang 453000 Henan Peoples R China

The occurrence of machine breakdowns is a frequent and dynamic phenomenon in the production process. The implementation of effective preventive measures can mitigate such events and result in reduced production costs. This paper investigates the distributed hybrid flow shop scheduling problem with machine breakdown (DHFSSPB) considering short maintenance time. The bi-population cooperative scatter search (BCSS) algorithm is proposed to address the DHFSSPB, wherein the search for the optimal scheduling sequence is transformed into genetic evolution aiming to obtain a gene chain with both minimum lower bound and minimum cost attributes. Firstly, the DHFSSPB problem is modeled through a combination of predictive maintenance strategy and rightshift rescheduling rule. Subsequently, a diversification approach is developed to facilitate attribute inheritance, enhance the efficiency of job allocation, and establish a reference set. The reference set is partitioned into two subpopulations based on lower bound attributes and cost attributes, respectively. The corresponding hybrid search strategies are designed to enhance the efficiency of job sorting and machine selection for subpopulations with distinct attributes. The cooperative evolution between subpopulations occurs through the competitive interaction and fusion of individuals. An enhanced reinforcement learning approach is proposed to expedite the acceleration of individual attribute evolution by leveraging evolutionary knowledge acquired from populations, thereby effectively guiding the evolutionary trajectories of individuals. Additionally, a method for evaluating the population during the learning process is developed based on problem characteristics to enhance learning efficiency. Experimental results demonstrate that BCSS outperforms the comparative algorithm in solving the DHFSSPB.

关键词： Distributed hybrid flow scheduling Machine breakdown Bi-population Learning mechanism scatter search algorithm

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An efficient scatter search algorithm to solve transmission expansion planning problem using a new load shedding index

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2014年第2期24卷 153-165页

作者： Habibi, M. R. Rashidinejad, M. Zeinaddini-Meymand, M. Fadainejad, R. Kerman Grad Univ Technol Kerman Iran Sahid Bahonar Univ Kerman Dept Elect Engn Kerman Iran

Transmission network expansion planning (TNEP) is one of the most important parts of power system studies. An optimal expansion of a transmission system should also capable of facilitating forecasted load patterns as well as future generation. Mathematically, TNEP is a mixed integer nonlinear programming as a non convex problem that can be solved by either conventional or heuristic optimization algorithms. This paper proposes a methodology for choosing the optimal transmission expansion plan considering less computational effort. The proposed methodology is composed from combination of Modified scatter search algorithm and Constructive Heuristic algorithm (CHA) considering New Load Shedding Index (NLSI). The proposed NLSI is implemented without generation rescheduling in order to decrease the number of linear programming obtaining an optimal solution. The algorithm is applied to different cases: Garver, 24-Bus IEEE systems and Southern Brazilian System of 46 Buses system. The simulation result shows a significant performance of the proposed method in comparison with some studies addressed in literature. Copyright (c) 2012 John Wiley & Sons, Ltd.

关键词： transmission network expansion planning scatter search algorithm new load shedding index

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Reconfiguration of Radial Electric Power Distribution System via a scatter search algorithm

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IEEE LATIN AMERICA TRANSACTIONS 2015年第4期13卷 1022-1028页

作者： Rupolo, D. Mantovani, J. R. S. Univ Estadual Paulista Julio de Mesquita Filho UN Ilha Solteira SP Brazil

In this paper, to solve the reconfiguration problem of radial distribution systems a scatter search, which is a metaheuristic-based algorithm, is proposed. In the codification process of this algorithm a structure called node-depth representation is used. It then, via the operators and from the electrical power system point of view, results finding only radial topologies. In order to show the effectiveness, usefulness, and the efficiency of the proposed method, a commonly used test system, 135-bus, and a practical system, a part of Sao Paulo state's distribution network, 7052 bus, are conducted. Results confirm the efficiency of the proposed algorithm that can find high quality solutions satisfying all the physical and operational constraints of the problem.

关键词： scatter search algorithm Distribution Power System Reconfiguration Exponential Load Model Node-depth Representation

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A scatter search algorithm with a novel solution representation for flexible open shop scheduling: a multi-objective optimization

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JOURNAL OF SUPERCOMPUTING 2021年第11期77卷 13115-13138页

作者： Behnamian, J. Memar Dezfooli, S. Asgari, H. Bu Ali Sina Univ Fac Engn Dept Ind Engn Hamadan Hamadan Iran

The flexible open shop scheduling problem is the combination of two classical open shop and a parallel machine scheduling problems. Due to the computational complexity of solving the open shop scheduling problem, so far, limited research has considered the assumption of flexibility in this problem. In this study, a bi-objective flexible open shop scheduling with independent setup time is considered. The considered objective functions are to minimize the maximum completion time of jobs and total tardiness. Using the first objective function, an attempt is made to balance the amount of workloads on the machines so that the completion time of the last job is minimized, while using the second one, from the customers' point of view, an attempt is made to reduce the amount of tardiness in delivery of jobs to the customers. Here, firstly, a mixed-integer nonlinear programming model is proposed. Then, to deal with the multi-objective problem, the weighted Lp-metric method is used. Since, this problem is a non-deterministic polynomial-time hard problem (NP-hard), a scatter search algorithm is developed to obtain near-optimal solutions in a reasonable time. In this regard, for the first time, a novel solution representation method is also presented. To ensure the efficiency of the proposed algorithm, the results were compared with NSGA-II using several instances. After analyzing the results using four evaluation metrics, it is observed that the scatter search algorithm performs better than the NSGA-II.

关键词： Scheduling Flexible open shop scatter search algorithm Solution representation Multi-objective optimization

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Using an enhanced scatter search algorithm for a resource-constrained project scheduling problem

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SOFT COMPUTING 2009年第6期13卷 597-610页

作者： Mobini, M. D. Mahdi Rabbani, M. Amalnik, M. S. Razmi, J. Rahimi-Vahed, A. R. Univ Tehran Dept Ind Engn Tehran 4563 Iran Univ Montreal Ctr Res Transportat Montreal PQ H3C 3J7 Canada

The resource-constrained project scheduling problem is one of the classical problems in the field of operations research. There are many criteria to efficiently determine the desired schedule of a project. In this paper, a well-known criterion namely project's makespan is considered. Due to the complexity of the problem, it is very difficult to obtain optimum solution for this kind of problems by means of traditional methods. Therefore, an enhanced scatter search, based on a new path relinking and two prominent permutation-based and crossover operators, is devised to solve the problem. In order to validate the performance of the proposed algorithm, in terms of solution quality, the algorithm is applied to various test problems available on the literature and the reliability of it, is compared with well-reported benchmark algorithms. The computational results reveal that the proposed algorithm has appropriate results in comparison with the existing benchmark algorithms.

关键词： Project scheduling Resource constrained Makespan scatter search algorithm Path relinking

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An implementation of modified scatter search algorithm to transmission expansion planning

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2012年第Sup1期20卷 1206-1219页

作者： Meymand, Majid Zeinaddini Rashidinejad, Masoud Khorasani, Hamid Rahmani, Mohsen Mahmoudabadi, Amin Sahid Bahonar Univ Kerman Dept Elect Engn Kerman Iran Univ Estadual Paulista Fac Engn Ilha Solteira Sao Paulo Brazil

Transmission network expansion planning (TNEP) is one of the most important tasks in the field of power systems, especially in deregulated power system environments. TNEP is a nonlinear mixed integer programming problem that can be solved via hybrid heuristic algorithms. This paper presents a modified scatter search algorithm (MSSA) to reinforce the ordinary scatter search algorithm (SSA) to be equipped for handling large scale transmission expansion planning (TEP) problems. The proposed methodology is based on the SSA, incorporating some improved strategies so as to decrease the number of linear programming problems required to be solved iteratively. In this study, it is shown that the MSSA can handle TEP problems faster than the ordinary SSA, as well as other implemented algorithms. Case studies and simulation results show the significant performance of the proposed method in comparison with some studies addressed in common literature.

关键词： Transmission network expansion planning scatter search algorithm VGS algorithm metaheuristic algorithm

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A scatter search algorithm for Multi-Criteria Inventory Classification considering Multi-Objective Optimization

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SOFT COMPUTING 2022年第17期26卷 8785-8806页

作者： Saracoglu, Ilkay Halic Univ Dept Ind Engn Istanbul Turkey SBB Danismanlik & Egitim Hizmetleri Ltd TR-34398 Istanbul Turkey

Inventory management requires thousands or millions of individual transactions each year. Classification of the items influences the results of inventory management. Traditionally, this is usually classified with considering an annual dollar usage criterion but maybe other criteria such as lead time, criticality, perishability, inventory cost, and demand type can be affected on that classification. Inventory items that have more than one criterion are discussed under multi-criteria inventory classification (MCIC) methods in the literature. In this paper, the MCIC problem is considered with two objectives as follows: (1) minimization of total inventory relevant cost and (2) minimization of the dissimilarity index. The proposed Mixed Integer Nonlinear Programming (MINLP) model of the MCIC problem is formulated using scatter search algorithm (SSA). The suggested multi-objective optimization problem is solved using LP-metric, e-constraint and weighted sum method. Pareto optimal solutions are obtained according to these different methods and selected best method by using deviation index. scatter search algorithm provides high-quality solutions within reasonable computation times. The proposed model generated a Pareto frontier solution with the maximum satisfaction level and minimum distance from ideal point. Finally, the proposed model is implemented with two numerical datasets to show the performance of its efficiency and compared our results with other studies in the previous literature.

关键词： Multiple criteria analysis ABC inventory classification scatter search algorithm Satisfaction level Multi-objective optimization

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An improved scatter search algorithm for the corridor allocation problem considering corridor width

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SOFT COMPUTING 2020年第1期24卷 461-481页

作者： Zhang, Zeqiang Mao, Lili Guan, Chao Zhu, Lixia Wang, Yi Southwest Jiaotong Univ Sch Mech Engn Chengdu Peoples R China Technol & Equipment Rail Transit Operat & Mainten Chengdu 610031 Peoples R China Auburn Univ Dept Math & Comp Sci Montgomery AL 36117 USA

In the existing literature on the corridor allocation problem (CAP), the corridor width is not taken into consideration. But in the actual production, the corridor width plays a very important role in logistics transportation inside factories. To study the effect of the corridor width in a CAP problem, the corridor width is considered by a mixed-integer programming model proposed in this paper. Subsequently, an improved scatter search (ISS) algorithm is proposed to handle the CAP. Several improvement mechanisms have been applied to the ISS according to the special characteristics of the problem, such as the adoption of a simulated annealing operation, a dynamic reference set update method, and an improved subset generation method. The proposed ISS is evaluated on test instances of various sizes ranging from 9 to 49 facilities. Computational results demonstrate the validity of the ISS. Specifically, for small-sized instances, the acquired best solutions by the ISS are identical to the optimal solutions obtained by the exact solution given by GUROBI, while for moderate and large-sized instances, the objective values by the ISS are better than those solved by the method in GUROBI. Furthermore, the proposed algorithm shows better performance in solution quality and stability by comparing to the simulated annealing algorithm and the scatter search algorithm.

关键词： Corridor allocation problem Facility layout scatter search algorithm Simulated annealing operation

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Hybrid Cooperative scatter search algorithm with Elite Learning Mechanism 4

Hybrid Cooperative Scatter Search Algorithm with Elite Learn...

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4th International Conference on Computer, Control and Robotics (ICCCR)

作者： Zhou, Gang Xie, Songbo Zhang, Xianxia Li, Ke Shanghai Univ Sch Mech & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai Peoples R China Shandong Laigang Yongfeng Steel Corp Dezhou Shandong Peoples R China

ISBN: (纸本)9798350373141;9798350373158

A novel hybrid cooperative scatter search (SS) algorithm with an elite learning mechanism (HSSA) is proposed for addressing complex continuous global optimization problems. The HSSA integrates the evolutionary mechanism of the backtracking search algorithm (BSA) into the reference set update process of SS. In addition, an elite individual-guided learning mechanism is proposed to guide the evolutionary direction of the population through the information provided by the current optimal individual. An opposition-based learning mechanism is adopted to avoid the population from falling into stagnation. Experimental results conducted on the CEC2017 benchmark test set demonstrate the effectiveness of the HSSA algorithm.

关键词： scatter search algorithm elite learning mechanism opposition-based learning global optimization

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Time Delay Estimation Using scatter search algorithm for Underwater Acoustic Channel

Time Delay Estimation Using Scatter Search Algorithm for Und...

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IEEE International Conference of Region 10 (TENCON)

作者： Zhang Chan Lei Zhixiong Yang Kunde Northwestern Polytech Univ Inst Acoust Engn Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9781479928255;9781479928279

To overcome the shortcoming of low resolution of the matched filtering method when estimating time delays, the WRELAX algorithm of the Nonlinear Least-Squares (NLS) parameters estimation problem is commonly used. However, the computing time of the WRELAX algorithm is long. In this paper, the scatter search (SS)-based WRELAX algorithm is applied in underwater acoustical channel computation. Multipath time delay estimation of a CW signal is calculated in Gaussian white noise channel with three SNR conditions of 20dB, 10dB, and 0 dB. Simulation results show that the SS-based WRELAX algorithm reaches a higher resolution than the conventional matched filtering method. Moreover, the SS algorithm can reduce the iteration number a lot comparing with the Gauss-Newton algorithm in the process of searching the minimum objective function value.

关键词： multipath time delay estimation scatter search algorithm WRELAX algorithm

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