4.6 Article

A Novel Metaheuristic Hybrid Parthenogenetic Algorithm for Job Shop Scheduling Problems: Applying an Optimization Model

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Interdisciplinary Applications

A survey of job shop scheduling problem: The types and models

Hegen Xiong et al.

Summary: This paper provides a comprehensive review of the types and models of job shop scheduling problem (JSSP) and analyzes and classifies its entities, attributes, assumptions, and performance measures. Through extensive statistics and analysis of published papers, promising research directions are identified.

COMPUTERS & OPERATIONS RESEARCH (2022)

Article Automation & Control Systems

A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem

Jun-Qing Li et al.

Summary: This study proposed an efficient optimization algorithm, IGSA, to solve the flexible job shop scheduling problem with crane transportation processes. The algorithm simultaneously minimizes the maximum completion time and energy consumptions. Unlike previous methods, the algorithm considers crane lift operations and balances exploration abilities and time complexity.

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2022)

Article Management

A matheuristic for parallel machine scheduling with tool replacements

Quang-Vinh Dang et al.

Summary: This paper addresses the scheduling problem of a set of tasks on identical parallel machines in a work center, considering the complex characteristics, objectives, and decision-making process, and proposes a mathematical model and a new matheuristic to solve the problem, demonstrating its superiority through empirical experiments.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2021)

Article Computer Science, Information Systems

Decomposition-Based Multi-Objective Optimization for Energy-Aware Distributed Hybrid Flow Shop Scheduling with Multiprocessor Tasks

Enda Jiang et al.

Summary: This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks (EADHFSPMT) and proposes a Novel Multi-Objective Evolutionary Algorithm based on Decomposition (NMOEA/D) to solve it. The algorithm includes special designs such as decoding scheme, local intensification operators, and dynamic adjustment strategy for weight vectors, which have been proven effective through extensive computational experiments. The NMOEA/D has superior performances compared to existing algorithms, as verified by statistical comparisons.

TSINGHUA SCIENCE AND TECHNOLOGY (2021)

Article Computer Science, Information Systems

Crystal Structure Algorithm (CryStAl): A Metaheuristic Optimization Method

Siamak Talatahari et al.

Summary: Metaheuristics are computational procedures that intelligently guide the search process through efficient exploration of the search space for optimization problems. In response to the increasing challenges posed by large data sets, there is ongoing efforts to enhance existing algorithms and develop new ones. A powerful and efficient metaheuristic algorithm typically relies on rich inspiration sources and precise mathematical models.

IEEE ACCESS (2021)

Review Computer Science, Information Systems

A review on genetic algorithm: past, present, and future

Sourabh Katoch et al.

Summary: This paper discusses recent advances in genetic algorithms, analyzing selected algorithms of interest in the research community. It helps new and demanding researchers gain a broader understanding of genetic algorithms. The review covers well-known algorithms, genetic operators, research domains, and future research directions in genetic algorithms.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

Article Computer Science, Artificial Intelligence

Modeling and multi-neighborhood iterated greedy algorithm for distributed hybrid flow shop scheduling problem

Weishi Shao et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Article Computer Science, Theory & Methods

Solving the dynamic energy aware job shop scheduling problem with the heterogeneous parallel genetic algorithm

Jia Luo et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2020)

Review Computer Science, Artificial Intelligence

Review of job shop scheduling research and its new perspectives under Industry 4.0

Jian Zhang et al.

JOURNAL OF INTELLIGENT MANUFACTURING (2019)

Article Computer Science, Information Systems

Logistics automation control based on machine learning algorithm

Xiaomo Yu et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2019)

Article Green & Sustainable Science & Technology

MILP models for energy-aware flexible job shop scheduling problem

Leilei Meng et al.

JOURNAL OF CLEANER PRODUCTION (2019)

Article Computer Science, Interdisciplinary Applications

Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints

Dai Min et al.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2019)

Review Automation & Control Systems

A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems

Kaizhou Gao et al.

IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2019)

Article Computer Science, Information Systems

Scheduling Jobs of Two Competing Agents on a Single Machine

Chen-Yang Cheng et al.

IEEE ACCESS (2019)

Article Computer Science, Interdisciplinary Applications

Metaheuristics for the job-shop scheduling problem with machine availability constraints

Karim Tamssaouet et al.

COMPUTERS & INDUSTRIAL ENGINEERING (2018)

Review Computer Science, Information Systems

A Review on Artificial Bee Colony Algorithms and Their Applications to Data Clustering

Ajit Kumar et al.

CYBERNETICS AND INFORMATION TECHNOLOGIES (2017)

Article Computer Science, Interdisciplinary Applications

A novel chemical reaction optimization for the distributed permutation flowshop scheduling problem with makespan criterion

Hafewa Bargaoui et al.

COMPUTERS & INDUSTRIAL ENGINEERING (2017)

Article Computer Science, Interdisciplinary Applications

A novel hybrid multi-objective immune algorithm with adaptive differential evolution

Qiuzhen Lin et al.

COMPUTERS & OPERATIONS RESEARCH (2015)

Article Engineering, Electrical & Electronic

An improved partheno genetic algorithm for multi-objective economic dispatch in cascaded hydropower systems

Jinlong Wang et al.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2015)

Article Computer Science, Information Systems

Solving Distributed and Flexible Job-Shop Scheduling Problems for a Real-World Fastener Manufacturer

Tung-Kuan Liu et al.

IEEE ACCESS (2014)

Article Automation & Control Systems

Benchmarking flexible job-shop scheduling and control systems

Damien Trentesaux et al.

CONTROL ENGINEERING PRACTICE (2013)

Article Engineering, Industrial

Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns

Jian Xiong et al.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2013)

Article Engineering, Industrial

Minimising makespan in distributed permutation flowshops using a modified iterated greedy algorithm

Shih-Wei Lin et al.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH (2013)

Article Engineering, Industrial

Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm

Nasr Al-Hinai et al.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2011)

Article Mathematics, Applied

A derivation of the number of minima of the Griewank function

Huidae Cho et al.

APPLIED MATHEMATICS AND COMPUTATION (2008)

Article Engineering, Electrical & Electronic

Parallelization of genetic algorithm with sexual selection

K Omori et al.

ELECTRICAL ENGINEERING IN JAPAN (2005)

Article Operations Research & Management Science

A note on the Griewank test function

M Locatelli

JOURNAL OF GLOBAL OPTIMIZATION (2003)