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To cope with growing passenger demand and to provide better services, increasing the number of trains is desired for certain lines. Maximum possible throughput of a line is often limited due to the limited number of platforms at the terminal, which was the case with two bullet-train lines originating from Tokyo. In these lines, there exists an intermediate station in the close vicinity of the terminal. This paper proposes a network-based optimization model to analyze the throughput of a line when turn-backs at the adjacent station are introduced to increase the line capacity.

Optimization of vehicle routes with delivery and pickup for a rental industry is considered. The company delivers to or pickups from customers rented products. Several types of products exist, and customers rent the specified number of products of the specific type. Time windows exist for delivery and pickup. There exist two sizes of vehicles, and their trips start from and end at depot and vehicles can make several trips during a day. Delivery must precede pickup on any trip of a vehicle. Capacity of vehicles depends on product type and also on how products are loaded on vehicles. Depending on demand quantity, split deliveries/pickups may be necessary. The company wants to minimize the total transportation cost. Based on the fact that the total number of distinct trips is rather small due to limited capacity of the vehicles, our solution strategy first enumerates all possible trips. Routes (i.e., collection of trips) are obtained by assigning trips to vehicles so that the total cost is minimized subject to constraints on demand, an upper limit on the number of trips per vehicle, and time compatibility of trips assigned to each vehicle. Since there exist many time compatibility constraints, the problem is first solved without them, we then check the compatibility and if necessary add compatibility constraints, and the problem is solved again until all routes become time compatible. Computational performance of the proposed solution approach is evaluated.

It is necessary for railway companies to construct daily schedules of assigning rolling stocks to utilization paths. A utilization path consists of a series of trains that a particular rolling stock performs in a day. A mixed integer programming model based on Lai et al. [1] is presented and is shown that straightforward applications of the model result in too much computational time and also inappropriate assignment schedules due to end effects. We show that the model can be modified to alleviate these difficulties, and also show that the repeated applications of the optimization model in the rolling horizon allow to generate a feasible assignment schedule for a longer period of time thus indicating the feasibility of the optimization approach.

We consider the allocation of a running time supplement to a railway timetable. Previously, Vekas et al. examined the optimal way to allocate the running time supplement. The uncertain disturbances in a railway were modeled using random variables. In their model, it was assumed that there was an upper limit to the total supplement, but its allocation was not restricted. In this paper, we suggest an improvement to the previous model and present a new stochastic programming model in which there is a constraint on the running time supplement allocated to each trip to minimize the expected delay. Then a solution algorithm to solve the problem is developed. In the previous model, allocation of the running time supplement was biased because it was not allocated to all trips. We balance the amounts of supplements for trips by adding upper and lower bounds. The fluctuations of the supplements for trips become small, and the probability of a delay decreases using our new model. Then the calculation times using the L-shaped algorithm and the former method solving a deterministic equivalent of large-scale problems are compared. It is shown that the large-scale problems can be solved effectively by using the L-shaped method.

An efficient simulation/optimization approach is presented for finding a dynamic dispatching priority in a static job shop environment under the presence of multiple identical jobs. The key ingredients of the proposed approach are (1) an efficient processingtime-based dispatching rule, (2) simulation of a job shop, and (3) a mechanism to “fake” (or modify) job processing times based on the information of job slack obtained from simulation. The paper presents an overall approach to fake processing times, and also identifies alternative strategies for algorithm design. Experimental results of the proposed approach yield a dispatching priority with more than 10% better due date performance than the priority generated by a good processing-time-based dispatching rule in roughly 20 simulation runs.

This paper presents a simulation-optimization approach to find an appropriate dispatching priority. The study is based on a detailed simulator for a module-type commercial FMS. Specifically, after presenting the basic configuration and fundamental control logic of the system together with its main characteristics as a special type of a job shop, an algorithm is presented which combines simulated annealing and simulation to explore a dispatching priority of operations that minimizes the total tardiness. Computational performance of the algorithm is presented which shows that good solutions can be obtained mostly after 300 iterations or so. The paper also compares the performance of the optimal" or near optimal dispatching priority generated by the proposed algorithm with those generated by standard dispatching rules. The results show that standard dispatching rules such as EDD and SLACK which take due dates into considerations perform moderately, but not extremely well. The results also show that some of the workload-based dispatching rules such as SPT work consistently well.

Described in this paper is an application of a discrete-event simulation model for the Mazatrol FMS system manufactured by Yamazaki Mazak, one of the leading machine tool companies in the world, to analyze various causes of machine idle times. The Mazatrol FMS is a module-type FMS which consists of the maximum of 8 horizontal machining centers, 1 to 4 load/unload stations, a stacker crane, pallet stockers among others. Presentation of a conceptual framework for the machine idle times and their causes is followed by detailed simulation results. Simulation indicates that the utilization of machining centers during the normal operating period is at least 92.7% and is reasonably high, under the conditions of enough work load for each machine and no equipment failure. It is also shown that the main causes of the machine idle times differ depending on the periods in which they occur during the entire makespan. The increase of routing flexibility, which is known to be an important factor for the reduction of the makespan, is found to give little effect on the machine utilization. On the other hand, the results show that the number of pallets is an important factor for high machine utilization. The simulation results are expected to provide useful information for efficient operation of FMSs in general, and of the Mazatrol FMS in particular. Suggestions are given on how simulation results could be used to improve the system utilization on the medium-range as well as the short-term planning of FMSs.

This paper describes how a dentist can use a new management tool, a computerized dental practice management game, to plan his or her own practice. After reviewing factors to be considered in planning a dental practice, we briefly describe the game with special emphasis on what it can and cannot do. After identifying the information required to make such an exercise useful in planning a specific practice, the paper gives an example that shows how the game can be so used.

Product transportation and storage in steel works are modeled in order to evaluate both facility specification and transportation rules. Discrete-event simulation together with mathematical optimization technique are carried out based on probability distribution which is determined by analysis of actual operating data. The model utilizes a combined network and discrete-event approach written under the SLAM II simulation language. Simulation results show that the proper configuration of facilities and suitabIe transportation rules contribute to the carriage efficiency and lead to the great reduction of transportation cost in steel works .

This paper describes the structure of a dental practice management game. The game covers a wide spectrum of management decisions in setting up and in running a dental practice. The decisions considered include practice location, the form of practice, staffing mix, salaries, and the purchasing or leasing of equipment. The game also covers major daily, monthly, and yearly decisions including forecasting patient load, economic analysis, and scheduling of patients, workers, and operatories. The paper also discusses the cost and time required to run the game. Many sample printouts are included.