Hybrid modeling for vineyard harvesting operations

Hiring workers under seasonal recruiting contracts causes significant variation of workers skills in the vineyards. This leads to inconsistent workers performance, reduction in harvesting efficiency, and increasing in grape losses rates. The objective of this research is to investigate how the variation in workers experience could impact vineyard harvesting productivity and operational cost. The complexity of the problem means that it is difficult to analyze the system parameters and their relationships using individual analytical model. Hence, a hybrid model integrating discrete event simulation (DES) and agent based modeling (ABM) is developed and applied on a vineyard to achieve research objective. DES models harvesting operation and simulates process performance, while ABM addresses the seasonal workers heterogeneous characteristics, particularly experience variations and disparity of working days in the vineyard. The model is used to evaluate two seasonal recruiting policies against vineyard productivity, grape losses quantities, and total operational cost.

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.

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.

Hospital processes within an integrated system view: a hybrid simulation approach

Processes in hospitals or in other healthcare institutions are usually analyzed and optimized isolated for enclosed organizations like single hospital wards or certain clinical pathways. However, many workflows should be considered in a broader scope in order to better represent the reality, i.e., in combination with other processes and in contexts of macro structures. Therefore, an integrated view is necessary which enables to combine different coherences. This can be achieved by hybrid simulation. In this case, processes can be modeled and simulated by discrete simulation techniques (i.e., DES or ABS) at the meso-level. However, holistic structures can be comfortably implemented using continuous methods (i.e., SD). This paper presents a theoretical approach that enables to consider reciprocal influences between processes and higher level entities, but also to combine hospital workflows with other subjects (e.g., ambulance vehicles).

An agent-based framework to study occupant multi-comfort level in office buildings

With the trend towards energy efficient buildings that diminish fossil fuel usage and carbon emissions, achieving high energy performance became a necessity. Allowing occupants to be actively involved during the design and operation phases of buildings is vital in fulfilling this goal without jeopardizing occupant satisfaction. Although different occupant behavior types were considered in prior research efforts, recent tools did not however examine simultaneously visual, thermal and acoustic comfort levels. This paper presents work targeted at efficiently studying occupant multi-comfort level using agent-based modeling with the ultimate aim of reducing energy consumption within academic buildings. The proposed model was capable of testing different parameters and variables affecting occupant behavior. Several scenarios were examined and statistical results demonstrated that the presence of different occupant behavior types is deemed necessary for a more realistic overall model, and the absence of windows results in an acoustic satisfaction with a decrease in (HVAC) use.

Improving patient access to a public hospital complex using agent simulation

This paper uses agent based simulation to assess the effect of redesigning the points of access to a major public hospital complex in Chile, where nearly 15,000 people will pass through daily. The study is carried out by simulating pedestrian traffic in order to calculate density maps and service levels in hospital access and ramps. The simulation allows us to evaluate the flow of people and assess the layout performance, by identifying high patient flow areas and congested pedestrian traffic zones. By using this approach, it is possible to suggest changes to the original design and to improve pedestrian flow at hospital access points and ramps. The suggested changes reveal that pedestrian indicators could be improved, which in turn would improve the level of satisfaction of patients, relatives, and hospital personnel. A higher satisfaction level would help to reduce stress linked to hospital facilities and crowded spaces.

Building a Simulation Model to Characterize Interacting Workflows and to Explore New Workflow Alternatives

Sortie Generation Rate (SGR) is an important metric for air dominance. Lockheed Martin must demonstrate that the Air System can fly the sorties during an allotted time and deliver the capability to the war fighter. Aircraft turnaround time- the time between when the aircraft touches down, refuels, rearms, and completes inspections in order to release the aircraft, to aircraft wheels up - plays an important role in achieving the SGR requirement.

Towards a Guide to Domain-specific Hybrid Simulation

The advantages of combined simulation techniques have been already frequently discussed and are well-covered by the recently published literature. In particular, many case studies have been presented solving similar domain-specific problems by different multi-paradigm simulation approaches. Moreover, a number of papers exist focusing on theoretical and conceptual aspects of hybrid simulation. However, it still remains a challenge to decide, whether combined methods are appropriate in certain situations and how they can be applied. Therefore, domain-specific user guides for multi-paradigm modeling are required combining general concepts and best practices to common steps. In this paper, we particularly outline three major processes targeting to define structured hybrid approaches in domain-specific contexts, and we focus on some practical issues aiming to a sustainable model development. Finally, an example hybrid methodology for problems in healthcare will be presented.

Using Simulation to Assist Recruitment in Seasonally Dependant Contact Centers

The weather is unpredictable and can have a large impact on the profitability of seasonal businesses, particularly if staffing requirements are highly temperature-dependent. In this paper we describe our efforts in developing a what-if analysis tool to assist affected Small and Medium Enterprises in determining the best case scenario for timing hiring new staff and deciding the optimum length of temporary employment contracts.

Iterative Simulation and Optimization Approach for Job Shop Scheduling

In this paper, we present an iterative scheme integrating simulation with an optimization model, for solving complex problems, viz., job shop scheduling. The classical job shop scheduling problem which is NP-Hard, has often been modelled as Mixed-Integer Programming (MIP) model and solved using exact algorithms (for example, branch-and-bound and branch-and-cut) or using meta-heuristics (for example, Genetic Algorithm, Particle Swarm Optimization and Simulated Annealing).