Multi-agent Optimization of the Intermodal Terminal Main Parameters: Research Based on a Case Study

Due to numerous uncertainties such as bad weather conditions, frequent changes in the schedules of vessels, breakdowns of equipment, port managers are aiming at providing adaptive and flexible strategic planning of their facilities, especially intermodal terminals (dry ports).

This research shows that the combination of the agent-based modeling with other simulation approaches simplifies the process of designing simulation models and increases their visibility. The developed set of models allows the researchers to compute the balanced values of the parameters. Consequently, it helps achieve effective operation of a seaport – intermodal terminal system. The provided case study on one of the busiest ports in China proves the adequacy and validity of the developed simulation models.

How Order Placement Influences Resource Allocation and Order Processing Times Inside a Multi-user Warehouse

This paper focuses on the influence of different order placement behavior of users on the allocation of common resources inside a multi-user warehouse. Furthermore, the interdependencies between one user’s resource usage on other users’ order processing time is investigated. For this objective, an agent-based simulation model has been developed, depicting a rectangular warehouse with two users and one order picker. Results show that different order placement behavior and resource usage of one user have a strong influence on order processing times of other users. Furthermore, by simulating uneven order placement by one user, it can be shown that peaks in order demand influence other user’s order processing times with a delay of up to two hours after the peak occurred. Thus, the results highlight the need for coordinated order placement of partners inside a multi-user warehouse.

Dynamic Behavioural Modeling, Simulation and Analysis of Household Water Consumption in an Urban Area: a Hybrid Approach

Pakistan is rapidly becoming a water stressed country, thus affecting people’s well-being. Authorities are faced with making drastic water conservation policies toward achieving effective management of available water resources and efficient water supply delivery coupled with responsible demand side management. Due to the lack of modern water metering in Pakistan, water consumption is not being accurately monitored. To achieve this goal, we propose a hybrid modeling and simulation framework, consisting of Agent-Based Modeling (ABM) paradigm that deals with the behavior and characteristics of individuals and System Dynamics(SD) paradigm that accounts for water flow dynamics. Our approach provides dual-resolution expressiveness suitable for replicating real-world urban infrastructure scenarios. The key objective of the research is to assist authorities to understand and forecast short-term and long-term water consumption through examining varying patterns of water consumption in different climates and thus improving demand side water usage dynamically subject to water supply availability.

A Comprehensive Electricity Market Model Using Simulation And Optimization Techniques

Worldwide Electrical Power Systems (EPSs) are faced with tremendous challenges because of the reduction of greenhouse gas emissions and the increasing number of renewables. EPS analysis can help to show future developments in an uncertain environment and is an important task for the assessment of greenhouse gas emissions. In order to perform such a complex analysis of future EPSs, a huge number of input parameters is needed. Moreover, technical and also economical processes have to be considered. Thereby, one major task is the modeling of electricity markets. In this paper, we present an approach for the modeling of the German EPS including electricity markets using hybrid simulation and mathematical optimization. We contribute an object-oriented electricity market model which can be utilized to study different exchange mechanisms and behavior patterns of generation unit operators. Simulation results show market results for different generation unit operators and realistic market prices.

Hybrid Simulation Challenges and Opportunities: a Life-cycle Approach

The last 10 years have witnessed a marked upsurge of attention on Hybrid Simulation (HS). The majority of authors define HS as a joint modelling approach which includes two or more simulation approaches (mainly Discrete Event Simulation, System Dynamics and Agent Based Simulation). Whilst some may argue that HS has been in existence for more than 5 decades, the recent rise tended to be more problem driven rather than technical experimentation. Winter Simulation Conference (WSC) 2015, 2016, 2017 have witnessed 3 panels on the purpose, history and definition of HS, respectively. This paper reports on a comprehensive review conducted by the panelists on HS and its applications.

Application of Hybrid Simulation Modelling for the Implementation of Job Rotation in a Feedmill

This paper promotes a unique system dynamics-discrete event simulation hybrid modelling framework. The way the hybrid model is developed is intended to simplify the modelling process and make the framework flexible to a variety of situations. In the current study, the framework is used to investigate the success possibility of introducing within-shift job rotation in the plant and its optimal frequency. The intention is to reduce worker exhaustion and by so doing increase productivity and manufacturing throughput.

Investment Risk Management and Simulation Software for Multi-period Acquisition Planning Under Deep Uncertainty

Acquisition planning involves decisions to be made regarding the number of assets to be acquired initially and the type and timing of replacement and upgrade actions to maintain performance measures efficiently. Acquisition planning is challenging for high-valued assets because of considerable uncertainties in their long-term life cycle. This article proposes an approach to determine which acquisition strategy—i.e. what initial number of assets, what number of new acquisitions, and in what time throughout a long-term planning period—can robustly fulfil multiple performance objectives in the face of plausible future scenarios.

A Simulation-Based Investigation of Freight Transportation Policy Planning and Supply Chains

Regional freight transportation policy planning is a difficult task, as few policy-planners have adequate tools to aid their understanding of how various policy formulations affect this complex, socio-technical system. In this paper, we develop a proof-of-concept model to simulate the impacts of public policies on freight transportation in a simulated region. We use the techniques of multi-disciplinary system design and optimization to analyze the formulation of regional freight transportation policies and examine the relative effects of policies and exogenous forces on the region in order to provide insight into the policy-planning process. Both single objective and multi-objective analysis is performed to provide policy-planners with a clear understanding of the trade-offs made in policy formulation.

Falling Off the Cliff? Increasing Economic Security for Low Income Adults as the Safety Net Shrinks

The public assistance system is supposed to offer a bridge between poverty and self-sufficiency. Families receive benefits such as Temporary Assistance for Needy Families (TANF) or Supplemental Nutrition Assistance Program (SNAP) to soften the impact of loss of income. The programs are intended to be limited in duration and provide a very modest amount of financial support. Some families are fortunate to also receive a housing voucher or a child care subsidy to help offset basic expenses. Eligibility for benefits varies by program and is based on different criteria, most of which are linked to personal income. This study asks: what happens when benefits are cut before individuals reach economic stability? This is frequently called the “benefits cliff.”