Masanori Takamoto

Zero-one quadratic programming algorithm for resource leveling of manufacturing process schedules

In industrial plant construction scheduling, it is necessary to minimize the fluctuation or the maximum peak of the fluctuation or the maximum peak value of the daily resources amount, which is calculated as the sum of daily resources for each process. Minimization of the fluctuation or the maximum peak value corresponds to leveling the pile of resources. To perform this resource leveling, we need to decide on an objective function which is a monotone function that simply increases with the degree of resources leveling and then solve the optimization problem by fixing the process start dates while minimizing the objective function. Industrial plant construction is, however, in many cases a large-scale scheduling with an entire period of more than 1000 days and more than 100 processes, so it is very difficult to obtain a global optimization solution. In this study, we have developed an algorithm which solves a large-scale optimization problem to level necessary resources. This algorithm can quickly search for a good suboptimal solution close to the global optimal solution of a 0-1 quadratic programming problem. The algorithm searches by repeating a pivot operation using variable selection rules for resources leveling. We applied this algorithm to large-scale scheduling for an actual plant construction schedule, and successfully obtained a practical suboptimal solution within a few minutes (CPU power: 28MIPS). The results suggest that the algorithm is practical for resources leveling of large-scale construction scheduling.

Development of a scheduling algorithm for resource leveling in local time intervals

A scheduling algorithm has been developed for resource leveling in a plant construction schedule. The algorithm facilitates resource profile smoothing as well as resource peak flattening, through a combination of global leveling with a variance-based performance index and local leveling. The local resource leveling, done after the global leveling, further improves minor fluctuations and local peaks in the resource profile that are insensitive to the variance-based performance index. The local resource leveling is based on two steps: definition of a target resource profile for chosen local time intervals; and heuristic optimization which shifts the resource profile towards the target curve. The scheduling algorithm developed has been experimentally applied to a practical problem of simulating a plant construction schedule with about 5000 tasks. It was confirmed from the numerical results that local resource leveling is a promising way to refine the resource profile after global resource leveling.

A design verification method for programmable controller software

The conditions under which sequentialized logic in software exhibits undesirable behavior are explored and a design verification method is proposed. The method consists of two steps. (1) Input signals to the extracted section of the sequential control diagram including a feedback loop, which cause three kinds of potential states, (a) reset failure, (b) set failure, and (c) simple delay, are applied to the feedback loop in order to evaluate a failure possibility. (2) The input signals that cause a failure of the circuit output are identified using a simulation technique of backward signal propagation. Experiments with a simple sequential circuit confirms that this method can detect all the conditions which lead to undesirable behavior.<<ETX>>