This paper introduces Embedded Deterministic Test (EDT) technology, which reduces manufacturing test cost by providing one to two orders of m& reduction in scan test data volume and scan test time. The EDT architecture, the compression algorithm, design flow, experimental results, and silicon implementation are presented.

Finding optimal solutions for job shop scheduling problems requires high computational effort , especially under consideration of uncertainty and frequent replanning. In contrast to computational solutions, domain experts are often able to derive good local dispatching heuristics by looking at typical problem instances. They can be efficiently applied by looking at few relevant features. Howeve...

This paper proposes monitoring dispatching system solution based on the internet of things, which is through the analysis for port’s current situation, system components, operation process, communication protocol and safety alarm, etc. The system can fulfill real-time precise positioning monitoring and dispatching for port’s mobile terminals, and also fulfill real-time monitoring and effective ...

The most common taxi operation service consists conventionally of cruising randomly around a city to search for passengers. Because of de-regulation policies, over-supply and high vacancy rates have caused inefficient operation and low performance in the taxi market. Therefore, this paper aims to create an innovative operational service and to evaluate the environmental benefits of this service...

In this paper, we study decentralized probabilistic job dispatching and load balancing strategies which optimize the performance of heterogeneous multiple computer systems. We present a model to study a heterogeneous multiple computer system with a decentralized stochastic job dispatching mechanism, where nodes are treated as M/G/1 servers. We discuss a way to implement a virtual centralized jo...

A hybrid flow shop (HFS) is a generalized flow shop with multiple machines in some stages. HFS is fairly common in flexible manufacturing and in process industry. Because manufacturing systems often operate in a stochastic and dynamic environment, dynamic hybrid flow shop scheduling is frequently encountered in practice. This paper proposes a neural network model and algorithm to solve the dyna...

The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching ru...

In this study, a genetic algorithm is applied to obtain the best combination of transportation parameters for vehicle dispatching. The searching mechanism based on genetic algorithm can find several feasible solutions of dispatching parameters to proceed with transportation plan within constrained conditions. Besides, the concept of fuzzy due time is applied to replace that of time window so as...

Priority-dispatching rules have been studied for many decades, and they form the backbone of much industrial scheduling practice. Developing new dispatching rules for a given environment, however, is usually a tedious process involving implementing different rules in a simulation model of the facility under study and evaluating the rule through extensive simulation experiments. In this research...

We consider a heterogeneous two-server system processing fixed size jobs. This includes the scheduling system, where jobs wait in a common queue, and the dispatching system, where jobs are assigned to server-specific queues upon arrival. The optimal policy with respect to the delay in both systems is a threshold policy characterized by a single parameter. In this special case, the scheduling an...