Parallelization of population-based multi-objective meta-heuristics: An empirical study

In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneously optimize all the objectives. However, the majority of this kind of problems cannot be solved exactly as they have very large and highly complex search spaces. Recently, meta-heuristic approaches have become important tools for solving multi-objective problems encountered in industry as well as in the theoretical field. Most of these meta-heuristics use a population of solutions, and hence the runtime increases when the population size grows. An interesting way to overcome this problem is to apply parallel processing. This paper analyzes the performance of several parallel paradigms in the context of population-based multi-objective meta-heuristics. In particular, we evaluate four alternative parallelizations of the Pareto simulated annealing algorithm, in terms of quality of the solutions, and speedup.     

Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing

We define events so as to reduce the number of events and decision variables needed for modeling batch-scheduling problems such as described in [15]. We propose a new MILP formulation based on this concept, defining non-uniform time periods as needed and decision variables that are not time-indexed. It can handle complicated multi-product/multi-stage machine processes, with production lines merging and diverging, and with minimum and maximum batch sizes. We compare it with earlier models and show that it can solve problems with small to medium demands relative to batch sizes in reasonable computer times.     

总延误问题顺时安排法的性能比

给定一组工件的加工时间与工期，要求确定这些工件在一台机器上的加．工排列，使相应的总延误达到最小，这就是总延误问题．该问题在近年已被证明是NP困难的．由Wilkermn和Irwin（1971），林勋（1983）等所研究的顺时安排法能得到相邻交换意义下的局部解．在本文中，我们进一步证明该算法能得到前移邻域意义下的局部解，并确定了该算法的性能比．     

The implementation of ab initio quantum chemistry calculations on transputers

Summary The RHF and geometry optimization sections of the ab initio quantum chemistry code, GAMESS, have been optimized for a network of parallel microprocessors, Inmos T800-20 transputers, using both indirect and direct SCF techniques. The results indicate great scope for implementation of such codes on small parallel computer systems, very high efficiencies having been achieved, particularly in the cases of direct SCF and geometry optimization with large basis sets.The work, although performed upon one particular parallel system, the Meiko Computing Surface, is applicable to a wide range of parallel systems with both shared and distributed memory.     

最小树的一般算法

本文根据设计并行算法的基本原则,给出了最小树的两个对偶定理.在此基础上,建立了两种对偶的同步并行算法的雏型.这两种算法恰恰在对偶的意义下,概括了以往的最小树算法.     

带到达时间的单机排序中的资源分配问题

讨论两个单机排序的资源分配问题1｜rj,pj=bj-ajuj,Cmax≤｜∑uj和1｜rj,prec,pj=bj-ajuj C max≤｜∑uj并给出求其最优资源分配的多项式算法.     

A Hybrid Approach to Scheduling with Earliness and Tardiness Costs

A hybrid technique using constraint programming and linear programming is applied to the problem of scheduling with earliness and tardiness costs. The linear model maintains a set of relaxed optimal start times which are used to guide the constraint programming search heuristic. In addition, the constraint programming problem model employs the strong constraint propagation techniques responsible for many of the advances in constraint programming for scheduling in the past few years. Empirical results validate our approach and show, in particular, that creating and solving a subproblem containing only the activities with direct impact on the cost function and then using this solution in the main search, significantly increases the number of problems that can be solved to optimality while significantly decreasing the search time.     

CDMA蜂窝移动通信系统中的无线资源管理算法研究

无线资源管理是CDMA蜂窝移动通信系统保证业务质量(QoS)和提高频谱利用率的关键技术，本文提出了CDMA系统中无线资源管理算法的一般模型，阐述了三种重要的无线资源管理算法，即功率控制算法、呼叫接纳控制算法和分组调度算法的主要研究情况，并分析了目前研究中仍然存在和需要解决的问题。     

SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES AND COMPRESSION COSTS （PART I：EQUAL TIMES AND COSTS）

Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by realloeating resources. In this paper, authors consider a machine scheduling problemwith controllable processing times. In the first part of this paper, a special case where the pro-cessing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O（n^2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case, An effective heuristic to the genera/ problem will be presented.     

The course scheduling problem at Lufthansa Technical Training

Lufthansa Technical Training GmbH (LTT) performs training courses for Lufthansa Technik AG as well as for several other international airlines. Courses of about 670 different types are offered of which several hundred take place each year. The course scheduling problem faced by LTT is to construct a yearly schedule which maximizes the profit margin incurred while meeting a variety of complex precedence, temporal, and resource-related constraints. A “good” operational schedule should also meet a number of additional subordinate objectives. We formalize the problem and develop a heuristic scheme along with several priority rules, as well as a local search algorithm to determine well-suited weights for weighted composite rules. The operational planning situation of 1996 served as our major test instance; additional test instances were constructed by modifying this data. Several computational experiments were carried out to evaluate the performance of the algorithms. It turned out that the best so-found schedule is substantially better in terms of the profit margin incurred than the solution manually constructed by LTT.