A note: Minimizing maximum earliness on a proportionate flowshop

Most classical scheduling objective functions have been studied in the context of a proportionate flowshop. In most cases, the solution was shown to be identical to that of the single machine version. In this note we introduce a rare case where the extension to a proportionate flowshop leads to a different solution. Specifically, we study the problem of minimizing maximum earliness. We show that the problem remains polynomially solvable, but the running time of our proposed greedy-type algorithm is larger than that of the single machine case.     

Minimising total tardiness in the m-machine flowshop problem: A review and evaluation of heuristics and metaheuristics

In this work, a review and comprehensive evaluation of heuristics and metaheuristics for the m-machine flowshop scheduling problem with the objective of minimising total tardiness is presented. Published reviews about this objective usually deal with a single machine or parallel machines and no recent methods are compared. Moreover, the existing reviews do not use the same benchmark of instances and the results are difficult to reproduce and generalise. We have implemented a total of 40 different heuristics and metaheuristics and we have analysed their performance under the same benchmark of instances in order to make a global and fair comparison. In this comparison, we study from the classical priority rules to the most recent tabu search, simulated annealing and genetic algorithms. In the evaluations we use the experimental design approach and careful statistical analyses to validate the effectiveness of the different methods tested. The results allow us to clearly identify the state-of-the-art methods.     

A tabu search approach to an urban transport problem in northern Spain

In this work we analyze an urban transport problem that the City Council of Burgos, a city in northern Spain, has posed to the authors. Given a fleet of buses and drivers, the problem consists in designing routes and assigning buses to the routes such that the service level is optimized. The optimality of the service level is measured in terms of the waiting time at the bus stops and the duration of the trip. Thus, the problem comprises two decision levels (route design and bus assignment) and differs from other urban transport models found in the literature. In order to solve the problem, we propose two algorithms: one with a local search strategy and another with a tabu search strategy. In both cases, the solutions of the two decision levels are modified in alternating steps. The proposed algorithms obtained significantly better results than the tools currently applied by the transport authorities. In addition, the solutions obtained are very robust with respect to variations on demand, as shown by the experiments.     

Minimizing the bicriteria of makespan and maximum tardiness with an upper bound on maximum tardiness

This paper studies the flowshop scheduling problem with a complex bicriteria objective function. A weighted sum of makespan and maximum tardiness subject to a maximum tardiness threshold value is to be optimized. This problem, with interesting potential applications in practice, has been sparsely studied in the literature. We propose global and local dominance relationships for the three-machine problem and a fast and effective genetic algorithm (GA) for the more general m$m$-machine case. The proposed GA incorporates a novel three-phase fitness assignment mechanism specially targeted at dealing with populations in which both feasible as well as infeasible solutions might coexist. Comprehensive computational and statistical experiments show that the proposed GA outperforms the two most effective existing heuristics by a considerable margin in all scenarios. Furthermore, the proposed GA is also faster and able to find more feasible solutions. It should be noted that when the weight assigned to maximum tardiness is zero, then the problem is reduced to minimizing makespan subject to a maximum tardiness threshold value. Heuristics for both problems have been provided in the literature recently but they have not been compared. Another contribution of this paper is to compare these recent heuristics with each other.     

Heavy-traffic analysis of mean response time under Shortest Remaining Processing Time

Shortest Remaining Processing time (SRPT) has long been known to optimize the queue length distribution and the mean response time (a.k.a. flow time, sojourn time). As such, it has been the focus of a wide body of analysis. However, results about the heavy-traffic behavior of SRPT have only recently started to emerge. In this work, we characterize the growth rate of the mean response time under SRPT in the M/GI/1 system under general job size distributions. Our results illustrate the relationship between the job size tail and the heavy traffic growth rate of mean response time. Further, we show that the heavy traffic growth rate can be used to provide an accurate approximation for mean response time outside of heavy traffic regime.     

Hybridizing the cross-entropy method: An application to the max-cut problem

Cross-entropy has been recently proposed as a heuristic method for solving combinatorial optimization problems. We briefly review this methodology and then suggest a hybrid version with the goal of improving its performance. In the context of the well-known max-cut problem, we compare an implementation of the original cross-entropy method with our proposed version. The suggested changes are not particular to the max-cut problem and could be considered for future applications to other combinatorial optimization problems.     

A local search based approach for solving the Travelling Thief Problem: The pros and cons

The Travelling Thief Problem (TTP) is a novel problem that aims to provide a benchmark model of combinatorial optimization problems with multiple interdependent components. The TTP combines two other well known benchmark problems: the Travelling Salesman Problem (TSP) and the Knapsack Problem (KP). The aim of this paper is to study the interdependence between the TTP's components, and how it makes solving each sub-problem independently from the other useless for solving the overall problem. A local search approach is proposed to solve the TTP. Two simple iterative neighborhood algorithms based on our approach are presented, analyzed, and compared to other algorithms. Initialization strategies are empirically investigated. The experimental results confirm that our approach was able to find new better solutions for many TTP instances.     

A tabu search/path relinking algorithm to solve the job shop scheduling problem

We present an algorithm that incorporates a tabu search procedure into the framework of path relinking to generate solutions to the job shop scheduling problem (JSP). This tabu search/path relinking (TS/PR) algorithm comprises several distinguishing features, such as a specific relinking procedure to effectively construct a path linking the initiating solution and the guiding solution, and a reference solution determination mechanism based on two kinds of improvement methods. We evaluate the performance of TS/PR on almost all of the benchmark JSP instances available in the literature. The test results show that TS/PR obtains competitive results compared with state-of-the-art algorithms for JSP in the literature, demonstrating its efficacy in terms of both solution quality and computational efficiency. In particular, TS/PR is able to improve the upper bounds for 49 out of the 205 tested instances and it solves a challenging instance that has remained unsolved for over 20 years.     

Self-adapting algorithm to fair time sharing in wireless access networks

To adapt the data rate in accordance with the quality of the link, the IEEE 802.11 standard proposes the variable rate shifting functionality. This intrinsic functionality of the 802.11 products progressively degrades the bit rate when a host detects unsuccessful frame transmissions. Furthermore, the basic CSMA/CA channel access method guarantees that the long-term channel access probability is equal for all hosts. When one host captures the channel for a long time because its bit rate is low, it penalizes other hosts that use the higher rate, inciting a performance overall degradation. We propose a self-adapting algorithm to improve resources shared among the active hosts in the hot spot, thus avoiding the performance degradation caused by one or more low-rate hosts. This algorithm aims at avoiding this performance degradation and the consequent waste of bandwidth. An extensive evaluation is performed depicting the improvement achieved.     

A multi-restart iterated local search algorithm for the permutation flow shop problem minimizing total flow time

A variety of metaheuristics have been developed to solve the permutation flow shop problem minimizing total flow time. Iterated local search (ILS) is a simple but powerful metaheuristic used to solve this problem. Fundamentally, ILS is a procedure that needs to be restarted from another solution when it is trapped in a local optimum. A new solution is often generated by only slightly perturbing the best known solution, narrowing the search space and leading to a stagnant state. In this paper, a strategy is proposed to allow the restart solution to be generated from a group of solutions drawn from local optima. This allows an extension of the search space, while maintaining the quality of the restart solution. A multi-restart ILS (MRSILS) is proposed, with the performance evaluated on a set of benchmark instances and compared with six state of the art metaheuristics. The results show that the easily implementable MRSILS is significantly better than five of the other metaheuristics and comparable to or slightly better than the remaining one.     

Web服务响应时间测试

随着Web服务技术的不断发展和广泛应用,需要运用测试技术来保障Web服务的正确有效运行,而Web服务响应时间则是评估Web服务质量最直观的一个参数.基于Apache axis,解析WSDL,用CTM产生有效测试例,实现Web服务的实时测试、不同站点测试、负载测试、平均响应时间测试.测试表明程序运行稳定,测试的结果为评估Web的服务质量提供了有力的参考.就授权测试、多个Web服务测试方面还需完善的工作做了进一步探讨和展望.     

磁阀式可控电抗器的响应时间研究

简要介绍了磁阀式可控电抗器(MCR)的结构和工作原理,通过对磁饱和技术进行分析,指出了影响磁阀式可控电抗器响应时间的直接因素,并据此提出了提高响应速度的方法以及这些方法的优劣性和可行性。     

Coordination mechanisms for selfish scheduling

In machine scheduling, a set of jobs must be scheduled on a set of machines so as to minimize some global objective function, such as the makespan, which we consider in this paper. In practice, jobs are often controlled by independent, selfishly acting agents, which each select a machine for processing that minimizes the (expected) completion time. This scenario can be formalized as a game in which the players are job owners, the strategies are machines, and a player’s disutility is the completion time of its jobs in the corresponding schedule. The equilibria of these games may result in larger-than-optimal overall makespan. The price of anarchy is the ratio of the worst-case equilibrium makespan to the optimal makespan. In this paper, we design and analyze scheduling policies, or coordination mechanisms, for machines which aim to minimize the price of anarchy of the corresponding game. We study coordination mechanisms for four classes of multiprocessor machine scheduling problems and derive upper and lower bounds on the price of anarchy of these mechanisms. For several of the proposed mechanisms, we also prove that the system converges to a pure-strategy Nash equilibrium in a linear number of rounds. Finally, we note that our results are applicable to several practical problems arising in communication networks.     

An efficient local search for minimizing completion time variance in permutation flow shops

This paper illustrates that by exploiting the structure of hard combinatorial optimization problems, efficient local search schemes can be designed that guarantee performance in solution quality and computational time. A two-phase local search algorithm is developed and applied to the permutation flow shop scheduling problem, with the objective of minimizing the completion time variance. New and significant analytical insights necessary for effectively solving the permutation flow shop problem are also presented and used in this research. Computational results indicate that for test problems, the local search obtained optimal solutions for many instances, within few seconds of CPU time. For other benchmark problems with jobs between 50 and 100, the proposed algorithm, ADJ-Reduced improved the existing best known values within a practical time frame.