Stochastic scheduling in an in-forest

Consider a problem of scheduling activities of a research and development project, where precedence relations of the activities constituting the project are represented by edges of an in-forest. Each activity is characterized by two parameters: a cost for attempting that activity and a probability that attempting the activity will lead to successful completion. The problem is to find a policy for attempting activities that minimizes the expected cost incurred until termination (successful completion of the project or the first activity failure). The main result of the paper is the design of an efficient algorithm to determine an optimal sequence in which to attempt the activities; a result which is established for linear and exponential utility functions. It is also shown that, unlike the related problem with out-forest precedence relations, there need not exist an optimal policy that is based on an index-rule for determining priority of edges by evaluating their successors.     

带重入的单台机排序问题

本文考虑带重入的单台机排序问题,重入是指每个工件在机器上加工不止一次.通过把重入模型转化为带平行链约束的排序问题,我们成功地获得了单机重入问题的两个目标函数的多项式时间最优算法,一个是总带权完工时间∑ωjCj,另一个是最大费用函数hmax.     

一个具有两类工件的多目标排序的多项式时间算法

本文考虑具有两个工件集的单机排序问题.第一个工件集J1以完工时间和为目标函数,第二个工件集J2以最大加权完工时间为目标函数.问题的目标是寻找一种排序,使得两个目标函数的加权和达到最小.本文证明该问题可在O(n1n2(n1 n2))时间内求解.     

Solving the short-term electrical generation scheduling problem by an adaptive evolutionary approach

In this paper, we introduce an adaptive evolutionary approach to solve the short-term electrical generation scheduling problem (STEGS). The STEGS is a hard constraint satisfaction optimization problem. The algorithm includes various strategies proposed in the literature to tackle hard problems with constraints such as: the representation used a non-binary coding scheme that drastically reduces the search space compared with the traditional evolutionary approaches. Specialized operators are especially designed for this problem and for this kind of representation, which also includes a local search procedure. Furthermore, the algorithm is guided by an adaptive parameter control strategy. We used some very well known benchmarks for STEGS to evaluate our approach. The results are very encouraging and we have obtained new better values for all the systems tested. Our aim here is to show that evolutionary approaches can be considered as good techniques to be used to solve real-world highly constrained problems.     

Lot sizing with inventory gains

The lot sizing problem with inventory gains generalizes the classical lot sizing problem to one in which stock is not conserved. Instances of this problem can be polynomially transformed into instances of the classical problem. The implications for problems involving different production capacity limitations, backlogging and multilevel production are discussed.     

A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem

Over the last decade, many metaheuristics have been applied to the flowshop scheduling problem, ranging from Simulated Annealing or Tabu Search to complex hybrid techniques. Some of these methods provide excellent effectiveness and efficiency at the expense of being utterly complicated. In fact, several published methods require substantial implementation efforts, exploit problem specific speed-up techniques that cannot be applied to slight variations of the original problem, and often re-implementations of these methods by other researchers produce results that are quite different from the original ones. In this work we present a new iterated greedy algorithm that applies two phases iteratively, named destruction, were some jobs are eliminated from the incumbent solution, and construction, where the eliminated jobs are reinserted into the sequence using the well known NEH construction heuristic. Optionally, a local search can be applied after the construction phase. Our iterated greedy algorithm is both very simple to implement and, as shown by experimental results, highly effective when compared to state-of-the-art methods.     

问题Pm|rj,B|∑Cj的多项式时间近似算法

本文针对同型机分批排序问题Pm|rj,B|∑Cj进行了研究,给出了该问题在批容量B及机器台数m为常数情况下的多项式时间近似算法(以下简称PTAS);在B为常数时设计出了问题1|rj,B|∑WjCj的计算时间更少的PTAS．     

An Algorithm for the Job Shop Scheduling Problem based on Global Equilibrium Search Techniques

The job shop scheduling problem is considered, and an algorithm based on the global equilibrium search method is proposed for its solution. Computational experiments using well-known benchmark problems are presented. Several new upper bounds for these problems are obtained.Research partially supported by NSF and AirForce grants.     

极小化最大完工时间的单机分批加工问题

本文考虑极小化最大完工时间的单机分批加工问题．设有n个工件和一台批加工机器．每个工件有一个释放时间和一个加工时间．批加工机器可以同时加工b(b相似文献   

Fluid approximation of a controlled multiclass tandem network

A two-station, four-class queueing network with dynamic scheduling of servers is analyzed. It is shown that the corresponding Markov decision problem converges under fluid scaling to a fluid optimal control model. The structure of the optimal policy for the fluid network, and of an asymptotically optimal policy for the queueing network are derived in an explicit form. They concur with the tandem μ-rule, if this policy gives priority to the same flow of customers in both stations. In general, they are monotone with a linear switching surface. This revised version was published online in June 2006 with corrections to the Cover Date.