abstract   background and purpose: traditional lecture-based teaching has been long used to transit theoretical knowledge to the participants. due to some problems of this didactic approach, some believe that integration within an active method is more valuable in nursing education. in this study, we hypothesized that integrating lecture-based teaching within clerkship course would enhance nurs...

Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...

This paper presents an agent-based service-oriented framework to address the challenges for integrating real time shop floor scheduling and control in a multi-workcell environment. The proposed framework enables shop floor to adapt to the changes in the environment dynamically. Shop floor scheduling and control can address dynamic changes either within a workcell, such as machine breakdowns, or...

This paper presents a new algorithm based on integrating Genetic Algorithms and Tabu Search methods to solve the Job Shop Scheduling problem. The idea of the proposed algorithm is derived from Genetic Algorithms. Most of the scheduling problems require either exponential time or space to generate an optimal answer. Job Shop scheduling (JSS) is the general scheduling problem and it is a NP-compl...

The job-shop scheduling problem has attracted many researchers’ attention in the past few decades, and many algorithms based on heuristic algorithms, genetic algorithms, and particle swarm optimization algorithms have been presented to solve it, respectively. Unfortunately, their results have not been satisfied at all yet. In this paper, a new hybrid swarm intelligence algorithm consists of par...

Considering the standard particle swarm optimization (PSO) has the shortcomings of low convergence precision in job shop scheduling problems, the job shop scheduling solution is presented based on improved particle swarm optimization (A-PSO). In this paper, the basic theory of A-PSO is described. Also, the coding and the selection of parameters as well as the decoding of A-PSO are studied. It u...

We consider a robotic ow shop model in which a single robot is responsible for the transportation of parts between machines. For reasons of simplicity, when the shop is to produce a large number of identical parts, the robot usually performs repeatedly a xed sequence of activities. This sequence of activities is called a 1-unit cycle if each execution of the sequence results in the production o...

The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the propos...

We study the special case of the m machine ow shop problem in which the processing time of each operation of job j is equal to p j ; this variant of the ow shop problem is known as the proportionate ow shop problem. We show that for any number of machines and for any regular performance criterion we can restrict our search for an optimal schedule to permutation schedules. Moreover, we show that...

SOMMARIO/ABSTRACT In this paper we report on the extension of the classical HTN planner SHOP to plan in partially observable domains with uncertainty. Our algorithm PC-SHOP uses belief states to handle situations involving incomplete and uncertain information about the state of the world. Sensing and acting are integrated in the primitive actions through the use of a stochastic model. PC-SHOP i...