Mariusz Balaban

Towards a theory of multi-method m&s approach: part III

This paper is the first from a series of papers that aim to develop a theory of multi-method M&S approach. The aim of this paper is to develop ontological basis for multi-method M&S approach. The first part of this paper discusses terms related to the use of more than a single modeling & simulation (M&S) method. This is to show the ontological ambiguity currently present within the M&S field in the context of using more than a single method. Next section provides the philosophical stance of the authors about the main terms in order to provide clarification and context of the term multi-method M&S approach. The last section takes these previous concepts and proposes a set of definitions relevant to a multi-method M&S approach, including its parent and derivative terms.

Exploration of purpose for multi-method simulation in the context of social phenomena representation

Difficulty of social phenomena representation can be related to limitations of used modeling techniques. More flexibility and creativity to represent social phenomena (an adequate mix of model scope, resolution, and fidelity) is desirable. The representation of social phenomena with a combination of different methods seems intuitively appealing, but the usefulness of this approach is questionable. Current view on the justification of multi-method has limitations in social science context, because it lacks a human dimension. This paper explores the literature that pertains to mixing methods, and displays current reasoning behind the use of the multi-method approach. The perspective on mixing methods from empirical social science projected onto M&S domain exposes high-level purposes related to representation of social phenomena with mixed method approaches. Based on the reviewed literature and qualitative analysis, the general view of ingredients for inferring purposefulness of the multi-method approach in the context of social phenomena representation is proposed.

Hybrid simulation: historical lessons, present challenges and futures

Hybrid Simulation comes in many shapes and forms. It has been argued by many researchers that Hybrid Simulation (HS) provides more and better insights into the real-life system as it allows modelers to assess its inherent problems from different dimensions. As a result HS is becoming an important field within the Modeling and Simulation arena. Yet we find that there is no clear and/or cohesive definition for it. Therefore, this panel paper aims to explore the concept of HS and its progression through the years. In doing so, we hope to lay out the underpinnings of a structured HS approach by providing historical narratives of the origins of hybrid models; the current challenges expressed by scholars; and future studies to ensure more focused development of a comprehensive methodology for HS.

Return to work behavior of people with disabilities: a multi-method approach

This paper discusses the development of a simulation model to mimic a return to work phenomenon of Social Security Disability Insurance (SSDI) enrollees in the United States. Agent Based and Bayesian Network methods are used within a multi-method simulation model to capture system conditions and enrollee behavior. Bayesian Network is used within an agent to represent enrollees decision to work. A developed simulation model can be used to investigate many aspects of the return to work phenomenon. The model is used to answer a sample research query that examines how the perception of an enrollee on work incentives related to health improvements, money, and vocational assistance can affect the return to work phenomenon for 18 to 39 year old SSDI enrollees (at enrollment). This is measured as the total percentage of population with benefits terminated for work.

Analysis of future UAS-based delivery

Commercial use of Unmanned Aerial System (UAS) has the potential to reshape the delivery market and to open new business opportunities to small businesses, e.g., local stores, pharmacies, restaurants, as well as to large international and national businesses and government entities, e.g., Amazon, Google, UPS, power companies, and USPS. Simulation models can examine the value added to current business operations, the effects of radical shifts in current operations, and the formation of new types of businesses. This paper presents an envisioned future UAS delivery business operation models and develops a theoretical constructive simulation model. The conducted simulation analysis based on full factorial design estimated causalities between multiple independent and dependent business and policy factors e.g. drone velocity, flying altitude, number of drones, delivery demand, route type, maximum drone fly-time, number of orders completed, time average drone density, order time, drone utilization, and reachability of customers.

Towards airspace rules for future UAS-based delivery

The growth of the nascent UAS industry will be affected by the airspace coordination rules between drones because these rules can impact business profitability. Few analyses have been reported to support design of commercial UAS operations in low-altitude commercial urban airspace. Analysis of minimum horizontal separation is critical for designing safe and efficient UAS delivery systems. In this paper a constructive simulation model is used to analyze and evaluate proposed UAS airspace traffic. A high density of delivery drones could create a bottleneck in a drone-based supply chain very quickly, especially when a high minimum horizontal separation standard is required. This paper proposes a simple idea on how to organize low-altitude UAS traffic, and evaluates the idea using a simulation model. Additional implications and future work needed in relation to UAS-based delivery are also discussed.