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Discrete Artificial Bee Colony Algorithm for Lot-streaming Flowshop with total flowtime Minimization

Chinese Journal of Mechanical Engineering 2012年第5期25卷 990-1000页

作者： SANG Hongyan GAO Liang PAN Quanke State Key Lab. of Digital Manufacturing Equipment & Technology Huazhong University of Science and Technology Wuhan 430074 China School of Mathematics Science Liaocheng University Liaocheng 252059 China School of Computer Science Liaocheng University Liaocheng 252059 China

Unlike a traditional flowshop problem where a job is assumed to be indivisible, in the lot-streaming flowshop problem, a job is allowed to overlap its operations between successive machines by splitting it into a number of smaller sub-lots and moving the completed portion of the sub-lots to downstream machine. In this way, the production is accelerated. This paper presents a discrete artificial bee colony （DABC） algorithm for a lot-streaming flowshop scheduling problem with total flowtime criterion. Unlike the basic ABC algorithm, the proposed DABC algorithm represents a solution as a discrete job permutation. An efficient initialization scheme based on the extended Nawaz-Enscore-Ham heuristic is utilized to produce an initial population with a certain level of quality and diversity. Employed and onlooker bees generate new solutions in their neighborhood, whereas scout bees generate new solutions by performing insert operator and swap operator to the best solution found so far. Moreover, a simple but effective local search is embedded in the algorithm to enhance local exploitation capability. A comparative experiment is carried out with the existing discrete particle swarm optimization, hybrid genetic algorithm, threshold accepting, simulated annealing and ant colony optimization algorithms based on a total of 160 randomly generated instances. The experimental results show that the proposed DABC algorithm is quite effective for the lot-streaming flowshop with total flowtime criterion in terms of searching quality, robustness and effectiveness. This research provides the references to the optimization research on lot-streaming flowshop.

关键词： lot-streaming flowshop scheduling artificial bee colony algorithm total flowtime

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A Speed-up Method for calculating total flowtime in permutation flow shop scheduling problem

A Speed-up Method for calculating total flowtime in permutat...

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第25届中国控制与决策会议

作者： Jun-hua Duan Yu-Jie Yang Kai-zhou Gao Jun-qing Li Quan-ke Pan School of computer science Liaocheng University Network and Informatin Center Liaocheng University State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University)

ISBN: (纸本)9781467355339

Permutation flow shop scheduling problem with total flowtime criterion has been increasingly dealt with in recent years. A number of heuristics and metaheuristics have been developed for this problem. However, the calculation of total flow time for job permutations spends too much computational time in the algorithms. To address to this problem, Li et al [OMEGA, 2009, 37:155-164] presented a general flowtime computing method and proved its effectiveness. This paper proposes an improvement for the general flowtime computing method. The computation experiments based on the well-known benchmarks are provided. It is shown that the presented speed-up method is of effectiveness for the problem considered.

关键词： Flow shop scheduling total flowtime speed-up heuristics

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Objective increment based metaheuristic for total flowtime minimization in no-wait flowshops

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Journal of Southeast University(English Edition) 2008年第2期24卷 168-173页

作者：朱夏李小平王茜东南大学计算机科学与工程学院南京210096

To solve the NP-complete no-wait flowshop problems, objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or worse than the original one is only evaluated by objective increments, instead of completely calculating objective values as the traditional algorithms do, so that the computational time can be considerably reduced. An objective increment-based hybrid genetic algorithm （IGA） is proposed by integrating the genetic algorithm （GA） with an improved various neighborhood search （VNS）as a local search. An initial solution generation heuristic（ISG） is constructed to generate one individual of the initial population. An expectation value-based selection mechanism and a crossover operator are introduced to the mating process. The IGA is compared with the traditional GA and two best-so-far algorithms for the considered problem on 110 benchmark instances. An experimental results show that the IGA outperforms the others in effectiveness although with a little more time consumption.

关键词： no-wait flowshops total flowtime objective increment hybrid genetic algorithm

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Hybrid evolutionary algorithm for no-wait flow shops to minimize makespan and total flowtime

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Journal of Southeast University(English Edition) 2008年第4期24卷 450-454页

作者：廖小平刘有根李小平河海大学计算机及信息工程学院南京210098 东南大学计算机科学与工程学院南京210096

The NP-hard no-wait flow shop scheduling problems with makespan and total flowtime minimization are considered. Objective increment properties of the problems are analyzed. A non-dominated classification method is introduced to class population individuals into Pareto fronts to improve searching efficiency. Besides investigating the crowding distance and the elitist solution strategy, two effective bi-criteria local search procedures based on objective increments are presented to improve searching effectiveness. Based on the properties and methods, a hybrid evolutionary algorithm is proposed for the considered problems and compared with the best existing algorithms. Experimental results show that the proposed algorithm is effective with high efficiency.

关键词： no-wait flow shop objective increment makespan total flowtime evolutionary algorithm

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A Genetic Algorithm for Permutation Flowshop Scheduling With total flowtime Criterion

A Genetic Algorithm for Permutation Flowshop Scheduling With...

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2011 Chinese Control and Decision Conference（CCDC）

作者： Jun-hua Duan is with the school of computer science,Liaocheng University,Liaocheng,China..Min Zhang is with the school of computer science,Liaocheng University,Liaocheng,China.Guang-Yu Qiao,China united network communications company limited liaocheng Branch.Jun-qing Li with the school of computer science,Liaocheng University,Liaocheng,China.

This paper presents a genetic algorithm （GA） for the permutation flow shop scheduling problem with the objective of minimizing total *** initialization method based on the LR heuristic is used to construct an initial population with a certain level of quality and diversity.A variable-neighborhood-search based local improvement is utilized to refine all the generated solutions in each generation.A comparative evaluation is carried out against some effective algorithms in recent *** results show that the proposed GA is very effective for the permutation considered.

关键词： Flowshop Genetic algorithm Evolutionary computing total flowtime

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An iterated local search algorithm for distributed permutation flowshop group scheduling problems with total flowtime minimization

An iterated local search algorithm for distributed permutati...

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第40届中国控制会议

作者： Hui Zhao Yu-Fan Liu Quan-Ke Pan Yuan-Zhen Li School of Mechanical and Electrical Engineering and Automation Shanghai University International School Beijing University of Posts and Telecommunications

Distributed permutation flowshop group scheduling problem(DPFGSP) is studied in this paper. This problem can be regarded as a combination of the distributed flowshop scheduling and group scheduling. An improved iterated local search(dILS)algorithm is proposed to minimize the total flowtime. First of all, we use a simple heuristic algorithm based on the famous NEH heuristics to generate an initial solution. Next, we use the solutions obtained from two different neighborhoods to perform an iterated local search. The acceptance criterion is the simulated-annealing type with a constant temperature. Finally, the proposed dILS algorithm is compared with the existing VND algorithm based on the 810 benchmark instances. The experimental results show that the proposed dILS algorithm has significant advantages in solving the DPFGSP under consideration.

关键词： Iterated local search Distributed permutation flowshop group scheduling total flowtime

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An iterated local search algorithm for distributed assembly permutation flowshop problem

An iterated local search algorithm for distributed assembly ...

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第三十九届中国控制会议

作者： Ying-Ying Huang Quan-ke Pan XiaoLu Hu M Fatih Tasgetiren Jiang-ping Huang School of Mechanical and Electrical Engineering and Automation Shanghai University China Rural Technology Development Center International logistics management department Yasar University

Nowadays,the distributed assembly permutation flowshop problem（DAPFSP） has important applications in *** this paper,we propose a group iterated local search（gILS） algorithm to solve the problem with total flowtime（TF） *** use the heuristic method based on a ascending order,which is originated from the *** order to simplify and optimize the algorithm,we introduce two kinds of local search methods based on products and jobs *** addition,considering the diversity of search area,we propose a probabilistic random selection based on the TF value and the number of iterations to determine the optimized *** criterion is a simple comparison to determine whether a new solution is acceptable or ***,we calculate 180 instances with our proposed algorithm and compare the results with those from the recent effective *** results verify the superiority of the presented gILS algorithm.

关键词： Distributed flowshop scheduling Assembly line scheduling Iterated local search total flowtime

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Q-learning Based Meta-heuristics for Solving Distribute Permutation Flowshop Problems

Q-learning Based Meta-heuristics for Solving Distribute Perm...

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第43届中国控制会议

作者： Hanxiang Zheng Kaizhou Gao Bohan Qiu Hui Yu Weiyu Tang Macau Institute of System Engineering Macau University of Science and Technology

This paper addresses the distributed permutation flowshop scheduling problems with minimize the total flowtime. First, a mathematical model is developed to describe the concerned problems. Then, three meta-heuristics, Jaya, artificial bee colony, and iterative greedy, and their variants are employed for solving the problems. To enhance the performance of the algorithms, six local search strategies and a Q-learning mechanism are designed. During the iterative process, Q-learning is used to guide algorithms selecting high-quality local search strategies. Finally, the comprehensive numerical experiments are conducted to evaluate the effectiveness of the proposed algorithms. The experimental results demonstrate that Q-learning-based local search strategies achieves can improve algorithms' performance.

关键词： Distributed permutation flowshop scheduling meta-heuristics total flowtime Q-learning

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An Enhanced Fruit Fly Optimization for the Flexible Job Shop Scheduling Problem with Lot Streaming

An Enhanced Fruit Fly Optimization for the Flexible Job Shop...

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第37届中国控制会议

作者： Tao Meng Jun-hua Duan Quan-ke Pan Qing-da Chen Ju-tao Guo School of Mechatronic Engineering and Automation Shanghai University School of Mathematical Science Liaocheng University Computer Center Shanghai University State Key Laboratory of Synthetic Automation for process Industries Northeastern University Shanghai Spaceflight Precision Machinery Institute

In this work, we propose an enhanced fruit fly optimization（En FFO） to solve the flexible job shop scheduling problem with the consideration of lot streaming, the criterion of which is total flowtime minimization. In En FFO, the multi-swarm scheme is utilized to balance the exploitation and exploration ability. To better match the two sub-problems in FJSP, we introduce new solution representation and decoding scheme. In addition, considering characteristics of multi-swarm FFO and FJSP, adaptive search scheme and information interaction tactics are presented to strengthen search performance of the algorithm. Finally, comparisons with recent algorithms verify the superiority of the proposed En FFO for the considered problem.

关键词： Fruit Fly Optimization Flexible Job Shop Scheduling Lot Streaming total flowtime Decoding Scheme

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