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1.
We address the problem of minimizing makespan on identical parallel machines. We propose new lower bounding strategies and heuristics for this fundamental scheduling problem. The lower bounds are based on the so‐called lifting procedure. In addition, two optimization‐based heuristics are proposed. These heuristics require iteratively solving a subset‐sum problem. We present the results of computational experiments that provide strong evidence that the new proposed lower and upper bounds consistently outperform the best bounds from the literature.  相似文献   

2.
We consider the problem of scheduling n identical jobs with unequal ready times on m parallel uniform machines to minimize the maximum lateness. This paper develops a branch-and-bound procedure that optimally solves the problem and introduces six simple single-pass heuristic procedures that approximate the optimal solution. The branch-and-bound procedure uses the heuristics to establish an initial upper bound. On sample problems, the branch-and-bound procedure in most instances was able to find an optimal solution within 100,000 iterations with n≤80 and m≤3. For larger values of m, the heuristics provided approximate solutions close to the optimal values.  相似文献   

3.
Uncertainty is an inevitable element in many practical production planning and scheduling environments. When a due date is predetermined for performing a set of jobs for a customer, production managers are often concerned with establishing a schedule with the highest possible confidence of meeting the due date. In this paper, we study the problem of scheduling a given number of jobs on a specified number of identical parallel machines when the processing time of each job is stochastic. Our goal is to find a robust schedule that maximizes the customer service level, which is the probability of the makespan not exceeding the due date. We develop two branch-and-bound algorithms for finding an optimal solution; the two algorithms differ mainly in their branching scheme. We generate a set of benchmark instances and compare the performance of the algorithms based on this dataset.  相似文献   

4.
This paper describes a new parallel algorithm for solving n-job, m-machine flow-shop problems. The algorithm is basically a parallelization of the usual branch-and-bound method. It also takes advantage of all search method to keep high efficiency of parallel processing, when the sub-problem becomes smaller than certain size. It is shown that its implementation on both nCUBE2 and LUNA88k2 gives very good performance characteristics.  相似文献   

5.
针对家纺企业车间调度的实际情况,建立了优先级特殊工艺约束下并行多机拖后调度模型,并提出一种新颖的人工免疫算法对其求解。该算法是依据生物的免疫机理,将目标函数作为抗原,将问题的解作为抗体,对抗体采用向量组编码的方式进行编码,通过克隆、变异及一种新颖的基于浓度的种群多样性更新选择方法,提高了种群多样性,并通过局部搜索改善了种群质量,加快了收敛速度。仿真结果表明,与遗传算法相比较,该算法能更快更准确地收敛到全局最优解。  相似文献   

6.
针对并行机多目标调度问题,以完工时间和总延迟时间最小为目标函数建立了数学模型,从而将具有解决复杂组合优化问题的非劣排序遗传算法NSGA2应用于求解多目标并行机调度问题。文中详细描述了用NSGA2算法求解并行机调度问题的步骤,并通过Matlab仿真,表明YhqNSGA2算法求解多目标并行机调度问题的可行性和有效性。  相似文献   

7.
一种求解同等并行机调度的混合量子衍生进化规划算法   总被引:1,自引:0,他引:1  
于艾清  顾幸生 《控制与决策》2011,26(10):1473-1478
针对带顺序相关建立时间的同等并行机调度问题的求解,提出一种新的混合量子衍生进化规划算法.该算法通过定义新的量子个体来表示调度问题中的工件排序,并定义了针对调度问题的量子旋转角,使个体向更好的解靠近.同时,针对并行机问题本身,改进了个体的编码方式和新的变异方法.为了验证算法的有效性和收敛性,采用不同规模的算例进行仿真实验.结果表明,即使在小种群情况下,算法所得解均优于基本进化规划求得的解.  相似文献   

8.
Research efforts on parallel exact algorithms for the 0–1 knapsack problem have up to now concentrated on solving small problems (at most 1,000 objects) and in many cases results have only been obtained by simulation of the parallel algorithm. After a brief review of a well known sequential branch-and-bound algorithm we discuss a new parallel algorithm for the 0–1 knapsack problem which exploits the potential parallelism that exists during the backtracking steps of the branch-and-bound algorithm. We report results for our parallel algorithm on a transputer network for problems with up to 20,000 objects. The speedup obtained is nearly linear for 2, 4, and 8 processors except when there is a strong correlation between the profit and weight of the objects.  相似文献   

9.
10.
周辉仁  郑丕谔 《计算机应用》2007,27(9):2273-2275
针对最小化完工时间的等同和非等同并行多机调度一类问题,提出了一种递阶遗传算法。该算法根据问题的特点,采用一种递阶编码方案,此编码与调度方案一一对应。用递阶遗传算法优化并行多机调度不需设计专门的遗传算子,操作简单。计算结果表明,递阶遗传算法是有效的,能适用于大规模等同和非等同并行多机调度问题。  相似文献   

11.
The list marking problem involves marking the nodes of an ℓ-node linked list stored in the memory of a (p, n)-PRAM, when only the position of the head of the list is initially known, while the remaining list nodes are stored in arbitrary memory locations. Under the assumption that cells containing list nodes bear no distinctive tags distinguishing them from other cells, we establish anΩ(min{ℓ, n/p}) randomized lower bound for ℓ-node lists and present a deterministic algorithm whose running time is within a logarithmic additive term of this bound. Such a result implies that randomization cannot be exploited in any significant way in this setting. For the case where list cells are tagged in a way that differentiates them from other cells, the above lower bound still applies to deterministic algorithms, while we establish a tight

bound for randomized algorithms. Therefore, in the latter case, randomization yields a better performance for a wide range of parameter values.  相似文献   

12.
In this paper we study the unrelated parallel machines problem where n independent jobs must be assigned to one out of m parallel machines and the processing time of each job differs from machine to machine. We deal with the objective of the minimisation of the maximum completion time of the jobs, usually referred to as makespan or Cmax. This is a type of assignment problem that has been frequently studied in the scientific literature due to its many potential applications. We propose a set of metaheuristics based on a size-reduction of the original assignment problem that produce solutions of very good quality in a short amount of time. The underlying idea is to consider only a few of the best possible machine assignments for the jobs and not all of them. The results are simple, yet powerful methods. We test the proposed algorithms with a large benchmark of instances and compare them with current state-of-the-art methods. In most cases, the proposed size-reduction algorithms produce results that are statistically proven to be better by a significant margin.  相似文献   

13.
资源受限工程调度问题的优化方法综述   总被引:8,自引:1,他引:8  
由于资源受限的工程调度问题在理论上和实际中具有重要意义,近年来,国内外关于这一问题的优化方法有了较大的发展,因此根据收集到的资料,对求解这一问题的分支定界算法、基于优先规则的启发式算法、样本算法以及智能优化算法的最新发展进行简要概述,并指出了该问题未来的研究方向.  相似文献   

14.
针对在特殊工艺约束下,非等同并行多机总完工时间最小和总拖后惩罚最小双目标调度问题(BOSP),设计了一个双目标调度模型,进而构造了一个基于向量组编码的遗传算法。此算法的编码方法简单,能有效地反映实际调度方案,收敛速度快。同时为了更好地适应调度实时性和解大型此类问题的需要,在基于遗传算法自然并行性特点的基础上,实现了主从式控制网络模式下并行遗传算法。仿真结果表明,此算法是有效的,优于普通的遗传算法,具有较高的并行性,并能适用于解大型此类调度问题。  相似文献   

15.
针对并行与分布式系统中的同型机调度问题,提出了一种改进蚁群算法。结合问题具体特点,给出了蚂蚁分配方案的生成策略,设计了一种新颖的基于任务适合度的信息素表示方法,以实现信息素的有效累积;改进了状态转移规则,通过对阈值的自适应调整使算法能根据搜索进度确定查找区域;在对信息素全局更新前,对每轮迭代获得的最好解进行变邻域搜索,避免算法陷入局部最优,提高收敛速度。仿真结果表明,改进算法有较强的寻优能力和稳定的求解质量。  相似文献   

16.
This paper presents a new recursive hybrid algorithm for training a radial basis function (RBF) network. The algorithm consists of a proposed clustering algorithm to position the RBF centres and the Givens least-squares algorithm to estimate the weights. This paper begins with a discussion about the problems of clustering in positioning RBF centres. Then a new clustering algorithm called adaptive fuzzy c-means clustering algorithm is proposed to reduce the problems. The capability of the proposed algorithm was tested to model three data sets: one simulated and two real data sets. It was found that the algorithm provided good performance. The performance of the algorithm was then compared with adaptive k-means, non-adaptive k-means and non-adaptive fuzzy cmeans clustering algorithms. Overall performance of the RBF network that used the proposed clustering algorithm was found to be much better than those that used other clustering algorithms. Simulation results also revealed that the algorithm was not sensitive to initial centres.  相似文献   

17.
针对家纺企业车间调度的实际情况,建立了一种产品优先级约束的模糊车间调度模型。在模型中,完工时间和交货期都是模糊的,交货期平均满意度最大为调度目标。基于此模型,提出了一种自适应的遗传算法,该算法通过比例选择及局部搜索保证种群的优良特性,并通过自动调节变异率和交叉率的方式保证种群的多样性,有效跳出局部收敛。仿真结果表明,自适应遗传算法能有效求解,并优于免疫遗传算法。  相似文献   

18.
In this paper, we study a scheduling problem on identical parallel machines, in which a processing time and a due date are given for each job, and the objective is to maximize the number of just-in-time jobs. A job is called just-in-time if it is completed exactly on its due date. We discuss the known results, show that a recently published greedy algorithm for this problem is incorrect, and present a new quadratic time algorithm which solves the problem.  相似文献   

19.
In this paper we prove an exponential lower bound on the size of bounded-depth Frege proofs for the pigeonhole principle (PHP). We also obtain an (loglogn)-depth lower bound for any polynomial-sized Frege proof of the pigeonhole principle. Our theorem nearly completes the search for the exact complexity of the PHP, as S. Buss has constructed polynomial-size, logn-depth Frege proofs for the PHP. The main lemma in our proof can be viewed as a general Håstad-style Switching Lemma for restrictions that are partial matchings. Our lower bounds for the pigeonhole principle improve on previous superpolynomial lower bounds.  相似文献   

20.
We present new and effective lower bounds for the resource constrained project scheduling problem. This problem is widely known to be notoriously difficult to solve due to the lack of lower bounds that are both tight and fast. In this paper, we propose several new lower bounds that are based on the concept of energetic reasoning. A major contribution of this work is to investigate several enhanced new feasibility tests that prove useful for deriving new lower bounds that consistently outperform the classical energetic reasoning-based lower bound. In particular, we present the results of a comprehensive computational study, carried out on 1560 benchmark instances, that provides strong evidence that a deceptively simple dual feasible function-based lower bound is highly competitive with a state-of-the-art lower bound while being extremely fast. Furthermore, we found that an effective shaving procedure enables to derive an excellent lower bound that often outperforms the best bound from the literature while being significantly simpler.  相似文献   

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