An Improved Discrete Particle Swarm Optimization for Tugboat Scheduling Problem in Container Terminal

Flow Shop ◽

Particle Swarm ◽

Optimal Solution ◽

Flow Shop Scheduling ◽

Computational Time ◽

Scheduling Problem ◽

Swarm Optimization ◽

Discrete Particle

In this paper, two types of discrete particle swarm optimization (DPSO) algorithms are presented to solve the Permutation Flow Shop Scheduling Problem (PFSP). We used criteria to minimize total earliness and total tardiness. The main contribution of this study is a new position update method is developed based on the discrete domain because PFSP is represented as discrete job permutations. In addition, this article also comes with a simple case study to ensure that both proposed algorithm can solve the problem well in the short computational time. The result of Hybrid Discrete Particle Swarm Optimization (HDPSO) has a better performance than the Modified Particle Swarm Optimization (MPSO). The HDPSO produced the optimal solution. However, it has a slightly longer computation time. Besides the population size and maximum iteration have any impact on the quality of solutions produced by HDPSO and MPSO algorithms

A hybrid discrete particle swarm optimization-genetic algorithm for multi-task scheduling problem in service oriented manufacturing systems

Journal of Central South University ◽

10.1007/s11771-016-3087-z ◽

2016 ◽

Vol 23 (2) ◽

pp. 421-429 ◽

Cited By ~ 6

Author(s):

Shan-yu Wu ◽

Ping Zhang ◽

Fang Li ◽

Feng Gu ◽

Yi Pan

Keyword(s):

Genetic Algorithm ◽

Task Scheduling ◽

Manufacturing Systems ◽

Particle Swarm ◽

Scheduling Problem ◽

Swarm Optimization ◽

Discrete Particle ◽

Service Oriented

Solving Task Scheduling Problem for Distributed Sensor Network with Discrete Particle Swarm Optimization

2009 Fifth International Conference on Natural Computation ◽

10.1109/icnc.2009.83 ◽

2009 ◽

Author(s):

Wenzhong Guo ◽

Qiaoyun Huang ◽

Guolong Chen ◽

Lun Yu

Keyword(s):

Sensor Network ◽

Task Scheduling ◽

Particle Swarm ◽

Scheduling Problem ◽

Swarm Optimization ◽

Discrete Particle ◽

Distributed Sensor ◽

Distributed Sensor Network

The Discrete Particle Swarm Optimization Algorithms For Permutation Flowshop Scheduling Problem

Jurnal Teknik Industri ◽

10.22219/jtiumm.vol20.no2.1-12 ◽

2019 ◽

Vol 20 (2) ◽

pp. 1

Author(s):

Ikhlasul Amallynda

Keyword(s):

Flow Shop ◽

Particle Swarm ◽

Optimal Solution ◽

Flow Shop Scheduling ◽

Computational Time ◽

Scheduling Problem ◽

Swarm Optimization ◽

Discrete Particle

In this paper, two types of discrete particle swarm optimization (DPSO) algorithms are presented to solve the Permutation Flow Shop Scheduling Problem (PFSP). We used criteria to minimize total earliness and total tardiness. The main contribution of this study is a new position update method is developed based on the discrete domain because PFSP is represented as discrete job permutations. In addition, this article also comes with a simple case study to ensure that both proposed algorithm can solve the problem well in the short computational time. The result of Hybrid Discrete Particle Swarm Optimization (HDPSO) has a better performance than the Modified Particle Swarm Optimization (MPSO). The HDPSO produced the optimal solution. However, it has a slightly longer computation time. Besides the population size and maximum iteration have any impact on the quality of solutions produced by HDPSO and MPSO algorithms

A discrete particle swarm optimization for lot-streaming flowshop scheduling problem

European Journal of Operational Research ◽

10.1016/j.ejor.2007.08.030 ◽

2008 ◽

Vol 191 (2) ◽

pp. 360-373 ◽

Cited By ~ 105

Author(s):

Chao-Tang Tseng ◽

Ching-Jong Liao

Keyword(s):

Particle Swarm ◽

Scheduling Problem ◽

Flowshop Scheduling ◽

Lot Streaming ◽

Swarm Optimization ◽

Discrete Particle ◽

Flowshop Scheduling Problem

Multiprocessor task scheduling problem using hybrid discrete particle swarm optimization

Sadhana ◽

10.1007/s12046-018-0984-x ◽

2018 ◽

Vol 43 (12) ◽

Cited By ~ 1

Author(s):

T Vairam ◽

S Sarathambekai ◽

K Umamaheswari

Keyword(s):

Task Scheduling ◽

Particle Swarm ◽

Scheduling Problem ◽

Swarm Optimization ◽

Discrete Particle ◽

Multiprocessor Task Scheduling

An Improved Discrete Particle Swarm Optimization for Berth Scheduling Problem

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.373-375.1192 ◽

2013 ◽

Vol 373-375 ◽

pp. 1192-1195

Author(s):

Dan Hua Huang ◽

Su Wang

Keyword(s):

Particle Swarm Optimization Algorithm ◽

Container Terminal ◽

Particle Swarm ◽

Mathematic Model ◽

Allocation Rule ◽

Scheduling Problem ◽

Swarm Optimization ◽

Berth Scheduling

Berth scheduling operation is an important problem in container terminal. The mathematic model of this problem is described in this paper and an improved particle swarm optimization algorithm is introduced to obtain the optimal scheduling solution. A floating-point allocation rule is used to encode the particles in the discrete space. A local search method is combined with PSO to avoid precocity. Finally the experiments are done to prove the improved PSO in this paper can resolve the berth scheduling problem and get better solution and convergence speed than the basic PSO.