Iterative Simulation and Optimization Approach for Job Shop Scheduling Ketki Kulkarni, Jayendran Venkateswaran, Indian Institute of Technology Bombay. Winter Simulation Conference, 2014.

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).
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Analysis of The Expansion of The Panama Canal Using Simulation Modeling and Artificial Intelligence L. Rabelo, L. Cruz, S. Bhide, O. Joledo, J. Pastrana, P. Xanthopoulos, University Of Central Florida. Winter Simulation Conference, 2014.

This paper presents preliminary analysis of the Panama Canal Expansion from the viewpoint of salinity in
the Gatun Lake and the utilization of neural networks. This analysis utilized simulation modeling and
artificial intelligence.
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Increasing rail capacity utilization in port of Hamburg by early provision of information for import containers Ralf Elbert, Fabian Walter, Chair of Management and Logistics, Technische Universität Darmstadt. AnyLogic Conference 2014.

Various actors are involved in hinterland transportation of incoming rail containers along the maritime transport chain. To coordinate each actor’s logistics processes, and therefore to improve utilization of existing transport capacity, the early provision of information, e.g. in form of estimated time of arrival (ETA), is inevitable.
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Simulating A Physical Internet Enabled Mobility Web: The Case Of Mass Distribution In France D. Hakimi, B. Montreuil, and others. 9th International Conference of Modeling, Optimization and Simulation

Physical Internet (PI) is a novel concept aiming to render more economically, environmentally and socially efficient and sustainable the way physical objects are transported, handled, stored, realized, supplied and used throughout the world. It enables, among other webs, the Mobility Web which deals with moving physical objects within an interconnected set of unimodal and multimodal hubs, transits, ports, roads and ways.
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Electric Vehicle Driver Simulation using Agent-Based Modeling Beaudry Kock, Recargo, Inc., 2014

Recargo has been developing an agent-based model with the AnyLogic tool to help us simulate the charging patterns of electric vehicle drivers in California. Our goal is to better understand the potential value from delivering electricity grid services with these vehicles. Development has only been underway for a few weeks, but in that time we’ve been able to use AnyLogic’s accessible interface and Java coding tools to quickly build and test a proof-of-concept model with which we can explore the potential for a more sophisticated and complex effort.
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Logistics Simulation and Optimization for Managing Disaster Responses F. Barahona, M. Ettl, M. Petrik, P.M. Rimshnick, IBM T.J. Watson Research Center, Proceedings of the 2013 Winter Simulation Conference

Catastrophic events such as hurricanes, earthquakes or floods require emergency responders to rapidly distribute emergency relief supplies to protect the health and lives of victims. In this paper we develop a simulation and optimization framework for managing the logistics of distributing relief supplies in a multi-tier supply network. The simulation model captures optimized stocking of relief supplies, distribution operations at federal or state-operated staging facilities, demand uncertainty, and the dynamic progression of disaster response operations. We apply robust optimization techniques to develop optimized stocking policies and dispatch of relief supplies between staging facilities and points of distribution. The simulation framework accommodates a wide range of disaster scenarios and stressors, and helps assess the efficacy of response plans and policies for better disaster response.
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Agent-Based Simulation for Dual Toll Pricing of Hazardous Material Transportation Sojung Kim, Santosh Mungle, Young-Jun Son, Proceedings of the 2013 Winter Simulation Conference

A dual toll pricing is a conceptual policy in which policy maker imposes toll on both hazardous materials (hazmat) vehicles as well as regular vehicles for using populated road segments to mitigate a risk of hazmat transportation. It intends to separate the hazmat traffic flow from the regular traffic flow via controlling the dual toll. In order to design the dual toll pricing policy on a highly realistic road network environment and detailed human behaviors, an extended Belief-Desire-Intention (BDI) framework is employed to mimic human decision behaviors in great detail. The proposed approach is implemented in AnyLogic agent based simulation software with using a traffic data of Albany, NY. Also, search algorithms in OptQuest are used to determine the optimum dual toll pricing policy which results in the minimum risk and travel cost based on the simulation results. The result reveals the effectiveness of the proposed approach in devising a reli-able policy under the realistic road network conditions.
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RoPax/RoRo: Exploring the Use of Simulation as Decision Support System Mariusz Balaban and Tom Mastaglio

Several challenges of port/terminal and/or ferry company managers pertain to decisions for the justification of investments and concurrent operational tasks of roll-on/roll-off passenger (RoPax) and roll-on/roll-off (RoRo) systems. This paper explores the possible uses of Modeling and Simulation (M&S) techniques as a decision-support aid for a RoPax/RoRo system managers.
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Modeling and simulation of container terminal logistics systems using Harvard architecture and agent-based computing Bin Li (Department of Economics and Management); Wen-feng Li (School of Logistics Engineering). Proceedings of the 2010 Winter Simulation Conference.

As the highly complex logistics system, container terminal logistics systems play an increasingly important role in modern international logistics, and therefore their scheduling and decision-making process of much significance to the operation and competitiveness of harbors. In this paper, the handling, stacking and transportation in CTLS are regarded as a kind of generalized computing and compared with the working in general computer systems, whereupon the Harvard architecture and AnyLogic agent-based computing paradigm are fused to model the operational processing of CTLS, and the kernel thoughts in computer organization, architecture and operating system are introduced into CTLS to support and evaluate container terminal planning, scheduling and decision-making.
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Supply chain and hybrid modeling: the Panama Canal operations and it’s salinity diffusion Mario Marin, Yanshen Zhu (American Technologika); Luz Alba Andrade, Erwin Atencio, Carlos Boya (Universidad La Latina); Carlos Mendizabal (Universidad Tecnologica de Panama). Proceedings of the 2010 Winter Simulation Conference.

This paper deals with the simulation modeling of the service supply chain and the salinity and its diffusion in the Panama Canal. An operational supply chain model was created using discrete-event simulation. Once complete, a component based on differential equations was added to the model to investigate the intrusion of salt and the resulting salinity diffusion into the lakes of the canal. This component was implemented in the AnyLogic simulation modeling environment by taking advantage of the concept of hybrid modeling that is embedded in AnyLogic.
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