Discrete Event Simulation DES Research Proposal

  • Length: 5 pages
  • Sources: 10
  • Subject: Anthropology
  • Type: Research Proposal
  • Paper: #30777411

Excerpt from Research Proposal :

Discrete-Event Simulation (DES)

Literature review and framework on Discrete-Event Simulation (DES)

Discrete event simulation is a significant method applied to establish the performance and dependability of diverse systems, which include computer and communication networks. Simulation study has become prominent in controlling human behavior. This has led to increased performance by the human through their behavior. Three approaches will be discussed in details with regard to discrete event simulation (Abu-Taieh 7). Resources involve people and machines used in ensuring work performance are achieved. It is through resources that an organization can achieve its intended objective when producing goods or services. Therefore, modeling a human as a resource means that a number of steps ought to be taken for instance, the flow of materials in a production process. People are thus considered to be resources in a modeling process, however; individual differences are not put into consideration (McGinnis, 23).

Greasily presented a discrete event simulation illustration through an arrest process in UK police service, the arrested person in this case is the customer, presented by an object (Greasley 534). The police personnel, on the other hand, is presented by a simulation. The simulation process is seen through the activities undertaken by the police personnel of either arresting or interrogating the individual. The method, therefore; allows people to be represented as resource objects and be scrutinized for factors for instance whether the utilization of resources through human behavior is similar to machines.

Another way of studying human behavior is through simplification where the human behavior is studied through elimination. The simplification method is useful because people are required to work without exhibiting human behavior of laziness and tiredness. In the model, human behavior is overlooked for instance, unanticipated absenteeism through sickness and family matters (Leemis and Stephen 34). Machines are modeled in such a way human behavior does not affect its operation to enhance productivity. Time and deadlines are incorporated to ensure human behavior does not interfere with work performance.

Externalizing human behavior outside the simulation process is also another method that can be used to access simulation process. In this case, not all-human behavior is incorporated in the study but only the complex human behavior; for example, decision-making. The decision-making ability is assessed in logic or probability form, to ensure the human behavior shown through decision-making is sensible and reliable (Pooch and James 11). Discrete event simulation is appropriate to modeling recognizable material, and people flow in an organization. However, decision-making process is not easily observable and is considered complex in an organization setting. In addition, when making strategic decisions external data is used this is different from the data used in the simulation information set.

The human behavior can be assessed through conversion of decision points and other concepts of the simulation model into parameters that need human contribution. The real performance of human behavior will be analyzed, and cost effective measures will also be applied. The decisions to be made should be incorporated in a simulation model, to ensure human behavior is exhibited accordingly. The simulation model can also be used as a recording tool, to develop a set of illustrations of human behavior at a decision point. The information will later be used as a representation of human behavior.

Task is also another approach of discrete event simulation of human behavior. The behavior of the human is determined base on the tasks performed. People are taken through a rigorous process where their behavior is monitored and observed for specific behavior. The process involves incorporating rules governing human behavior and simulation characteristics. Attributes such as skill level, the length of the task and perceived quality of the task to the organization are also assessed (Johnson and Mackulak 2173).

According to Freudenberg and Herper (951) they described the level of abstraction needed to assess diverse working structures. They claimed that workers should be modeled in a material flow system. In addition, to ensure employees work accordingly, time management should be respected and the workers work performance should be controlled accordingly. A central disposition approach should be applied. In this case, each worker is expected to transmit traits that show their job role, qualifications skills and time mode. The time model is expected to cover the breaks and shift patterns of every worker. The resources used in undertaking diverse tasks should be allocated to workers in accordance to their qualifications and capability to complete tasks. Simulation model is used to allocate the number of workers to a certain tasks in accordance to complexity. The model handles this approach incorporate materials and tasks as one entity, but when it comes to material flow and worker distribution to tasks differently. The approach is set to be best applied in modeling group works and paper investigates. The workers are grouped according to their qualifications and skills that relate to the tasks.

Dahn and Laughery (815) recognize the variability of human performance as a main obstruction to the inclusion of humans in simulation models. Discrete event simulation is applied to ensure human performance is measured when undertaking tasks. The model especially measures multiple tasks performed by humans. At times, multiple tasks reduce the level of performance of workers. Therefore, the model is used to determine whether the employees can manage multiple tasks. The technique assumed that excessive human workloads are not caused by undertaking one task but multiple tasks concurrently. Benchmark scales are used to determine workload by in diverse scenarios. Therefore, according to Laughery performance of work by humans can be determined by the multiple tasks undertaken (Laughery 817). In this approach, human capability with regard to tasks is measured and assessed accordingly. The approach claims that people to rest thus, when allocating tasks rest should be put into a consideration, to increase performance.

The approach also required workers the study workers through a simulation method on how they carried out multiple tasks. The first approach of the study involves putting resources in a pool where workers within the pool have the power to select any task from the pool. In addition, once a task has been initiated it ought to be completed without further delays. People are represented as entities rather than resource pools and tasks are divided into sessions. Whereby after all sessions objectives assessed whether they have been achieved or not. According to the approach, tasks are divided in accordance to the time limit, level of complexity and the demand for the task. Therefore, different mechanisms are applied to ensure the tasks are completed within the required time. Workers performance in this approach can be determined by the time taken to complete the work and the length of the task. The significance of customers with regard to the task also put into consideration, to ensure customer satisfaction is respected and achieved.

Juran and Schruben (257) claim the requirement for the appropriate representation of the individual worker behavior. Simulation method is applied through probability distribution method and using parameters to determine the probability. The approach is based on how humans behave and with regard to perception and attention. The modeling approach is said to be time driven and ensures goals are achieved. Through the approach, human behavior is determined and monitored to maximize on performance. According to Brailsford and Schmidt (20) simulation model can also be used to measure physical and emotional states of humans. The approach measures human behavior at an individual level. The psychological state of a person assessed and analyzed according to diverse attributes in order to come up with different emotions. Therefore, diverse objectives can be applied when incorporating human behavior in a simulation study.

The range of approaches has provided a framework for the diverse approaches of discrete event simulation. When undertaking simulation study human behavior is put under considerations. Study objectives are set to ensure results are achieved, and human behavior with regard to diverse tasks is understood. Discrete value simulation is the main approach applied to determine human behavior in different scenarios. Study of human behavior is significant in ensuring organizational tasks are achieved. In addition, workers performance in an organization setting is crucial, therefore; studying human behavior to monitor performance is also crucial. Workers need to rest occasionally, simulation approach ensures workers performance is measured and determined to ensure high performance is maintained, and worker's satisfaction is achieved. Workers advocating to work in multiple tasks should be assessed to determine whether a worker is capable of performing the tasks. Multitasking is a practice encouraged to be practiced in the workplace; however, the amount of work given to workers should be assessed to avoid overworking the workers and to provide them time for relaxation. Discrete event simulation model is applied to ensure the human behavior of employees at the work place is monitored to increase productivity. The study also assists an organization in grouping tasks, to employees in accordance to skills and capability. Therefore, simulation approach can be used in an organization setting to study human behavior through their working skills and capability and also through…

Cite This Research Proposal:

"Discrete Event Simulation DES" (2012, May 28) Retrieved January 19, 2017, from

"Discrete Event Simulation DES" 28 May 2012. Web.19 January. 2017. <

"Discrete Event Simulation DES", 28 May 2012, Accessed.19 January. 2017,