This paper discusses a vehicle routing problem for a permutation circulation-type vehicle routing system. In the system, several stages are located along by a single loop, and a fleet of vehicles travel on the loop unidirectionally and repeatedly. Traveling on the loop, each vehicle receives an object from the loading stage and then carries it to a certain processing stage, or receives an object from a certain processing stage and then carries it to the unloading stage per a turnaround. No passing is allowed for the vehicles on the loop. This paper proposes a heuristic algorithm for operating the system, which intends to reduce interferences between the vehicles. This paper also gives the numerical results with respect to the performance measures of the system such as the mean travel time of vehicles and the throughput of the system.
The performance of the Cell Array's structure for the Dynamically Reconfigurable Cell-Array Processor (DRCAP), which we first proposed in 1997, in actual program execution is examined. In the DRCAP, the processing of c-language program sentences, such as “if” and “for”, is remarkably accelerated by applying the pipeline or the parallel operation to repeating calculations. The performance of the Cell Array's structure in actual program execution is evaluated for the MPEG de-quantization process. It is found that a processing rate 30 times as higher as those in the conventional microprocessors can be realized in the present DRCAP.
Aiming at elimination of tardy jobs in a job shop production schedule, a simulation-based scheduling method with functions to control job allocation and capacity addition is proposed. In order to determine pertinent additional capacities and to control job allocations simultaneously, the proposed method incorporates the parameter-space search improvement (PSSI) method in which four parameters are introduced into the scheduling procedure. Furthermore, the proposed method adopts a local search method in order to reduce the computation time to search for the best solution on the parameter space. Performances of the proposed method with respect to the reduction of tardy jobs and the computation time are evaluated not only on a simple job shop model but also by using practical planning condition data prepared for an actual scheduling system. The results show that the proposed method gives significant performance for reducing tardy jobs as well as the amount of additional capacities and it is available for practical use.
The least mean square (LMS) algorithm has been widely used in adaptive signal processing applications, because of its simplicity and low complexity. This paper proposes a design method for an LMS-type algorithm which is robust in some sense and converges faster than the conventional LMS algorithm. The design problem is reduced to a semidefinite program which is an efficiently solvable optimization problem. Moreover the proposed design method is extended to the filtered-X LMS algorithm for active noise control, and an experimental result is provided to illustrate the effectiveness of the proposed method.
This paper describes how people establish or fail to establish long-run cooperation in the Prisoner's Dilemma Network (PDN), where subjects are allowed to nominate a subject with whom they want to play the Prisoner's Dilemma (PD) game at the beginning of each round. We have done a series of experiments with undergraduates and computer simulations of the PDN games. In the experiments most subjects either continued to play the PD game cooperatively with the same partner or never played the PD game cooperatively in the long run, and those who were more cooperative earned more. Since the simulations reproduced the results of the experiments, we can guess the subjects' strategies, which were not as apparent and controllable as the programs of agents.
This paper is concerned with a model reduction method taking account of the steady-state gain, while keeping the H∞ norm of the associated error system as small as possible with the LMI optimization technique. Taking account of the steady-state gain leads to decreasing the integrated square error between the step response of the original system and that of the reduced order system. The proposed method is applied to the reduction of the model of a multi-machine electric power system to demonstrate its effectiveness.
This paper proposes a fast method, called cyclic optimal multi-step method, for searching nearest target object in the road network under the spatial database, in which both target objects and road network are indexed by R-trees. This method consists of filtering and refinement steps, which run cyclically. By using this method, the nearest search begins from selecting a target with the shortest straight-line, measured from a source, as the candidate for path search and then determines a search region which contains the selected candidate target and road-based path. To implement this method, a priority queue is introduced to record nodes of R-tree and candidate objects, and also a variable which indicates the radius of search region is done to record the mediate results in searching the minimum path. In this case, the key by which the elements on the queue are to be ordered is the distance from the source object. Since in our method the path search process is limited only inside the search region and moreover only the object located at the head of the queue is considered, the search process is greatly accelerated.