Agent-based Analysis of Picker Blocking in Manual Order Picking Systems: Effects of Routing Combinations on Throughput Time Ralf Elbert, Torsten Franzke et al

Order picking is one of the most labor- and time-consuming processes in supply chains. Improving the performance of order picking is thus a frequently researched topic. Due to high cost pressure for warehouse managers the space in storage areas has to be used efficiently. Hence narrow-aisle warehouses where order pickers cannot pass as well as several order pickers working in the same area are common. This leads to congestion which is in this context referred to as picker blocking. This paper employs an agent-based simulation approach to investigate the effects of picker blocking in manual order picking systems with different combinations of routing policies for three order pickers in a rectangular warehouse with narrow-aisles.
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Agent-based Simulation of the Diffusion Dynamics and Concentration of Toxic Materials From Quantum Dots-based Nanoparticles Datu Buyung Agusdinata

Due to their favorable electrical and optical properties, quantum dots (QDs) nanoparticles have found numerous applications including nanomedicine. However, there have been concerns about their potential environmental impacts. The objective of this study is to develop an agent-based simulation model for predicting the diffusion dynamics and concentration of toxic materials released from QDs. Reaction kinetics is used to model the stability of surface capping agent particularly due to oxidation process.
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Strategic Planning of Logistics for Offshore Arctic Drilling Platforms Supported by Simulation Andrey A. Malykhanov, Vitaliy E. Chernenko

The operation of offshore drilling platforms requires a lot of logistics: supply of platforms by platform supply vessels (PSVs), backward transportation of waste in containers and transportation of oil by tankers to export ports. The severe weather conditions of the Arctic Ocean increase the number of possible disruptions that influence the logistic system. The operation of PSVs and tankers has multiple constraints and interactions. An agent-based simulation has been developed in AnyLogic to support the strategic planning of logistics by year 2042. The presentation discusses the use of the model to determine the required number of vessels and compare different options of crude oil outbound logistic network design.

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Particle Filtering Using Agent-based Transmission Models Kurt Kreuger, Nathaniel Osgood

Dynamic models are used to describe the spatio-temporal evolution of complex systems. It is frequently difficult to construct a useful model, especially for emerging situations such as the 2003 SARS outbreak.Here we describe the application of a modern predictor-corrector method – particle filtering – that could enable relatively quick model construction and support on-the-fly correction as empirical data arrives.
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An Agent-based Approach for Modeling the Effect of Learning Curve on Labor Productivity H. Shehwaro, E. Zankoul, and H. Khoury

The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Although previous research efforts developed models to represent the learning curve effect using traditional simulation approaches such as System Dynamics (SD) and Discrete Event Simulation (DES), none of these studies used Agent-Based Modeling (ABM) techniques. This study takes the initial steps and presents work targeted at analyzing the effect of learning on labor productivity using ABM.
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Use of agent-based modelling to predict benefits of cleaner fish in controlling sea lice infestations on farmed Atlantic salmon M.L. Groner, R.Cox, G.Gettinby and C.W. Revie

Sea lice, Lepeophtheirus salmonis, are ectoparasites of farmed and wild salmonids. Infestations can result in significant morbidity and mortality of hosts in addition to being costly to control. Integrated PEST management programmes have been developed to manage infestations, and in some salmon farming areas, these programmes include the use of wrasse. To explore at what densities wrasse should be stocked in order to meet specific control targets, an individual-based model was built to simulate sea lice infestation patterns on a representative salmonid host. It was found that the wrasse can effectively control sea lice, and the densities of wrasse needed for effective control depend upon the source of the infestation and the targeted level of control.
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Simulating Construction Bidding Using Agent-Based Modeling Sadegh Asgari, Ali Shafaat

Competitive bidding is the main mechanism for allocation of construction projects and consequently price determination of the construction services in the A/E/C industry. While different aspects of construction bidding have been studied in the literature, there is still a need for developing a comprehensive model that captures the complex dynamics of bidding environment by considering interactions among its components, most importantly construction contractors. This paper discusses the advantages of agent-based modeling in simulating the construction bidding process over the previously applied methodologies.
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Agent-based population model used to identify and evaluate dog population management strategies L. Kisiel, A. Jones-Bitton, A.L. Greer; Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON Canada; CEFUTREMA

Developing countries are faced with finding novel and humane ways to permanently reduce and control their dog population. Agent-based models developed to describe dog populations represent a unique, platform for using computer based simulation to identify control strategies with the greatest potential for success, aid in the design of more effective control measures, and provide a means to evaluate the success of different interventions.
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A Plant-Level, Spatial, Bioeconomic Model Of Plant Disease Diffusion And Control: Grapevine Leafroll Disease Shady S. Atallah, Miguel I. Gómez, Jon M. Conrad, and Jan P. Nyrop, University of New Hampshire

Grapevine leafroll disease threatens the economic sustainability of the grape and wine industry in the United States and around the world. This viral disease reduces yield, delays fruit ripening, and affects wine quality. Although there is new information on the disease spatial-dynamic diffusion, little is known about profit-maximizing control strategies. Using cellular automata, we model the disease spatial-dynamic diffusion for individual plants in a vineyard, evaluate nonspatial and spatial control strategies, and rank them based on vineyard expected net present values.
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A heuristic approach taking operators’ fatigue into account for the dynamic assignment of workforce to reduce the mean flowtime A. Ferjani, A. Ammar, H. Pierreval, A. Trabelsi, Clermont University

In order to cope with the frequent unpredictable changes that may occur in manufacturing systems, and to optimize given performance criteria, the assignment of workers can be decided online in a dynamic manner, whenever the worker is released. Several studies, in the ergonomics literature, have shown that individuals' performances decrease because of their fatigue in work. In manufacturing context, the workers’ fatigue impacts the task durations. Therefore, we propose to solve the online workers assignment problem through a heuristic, which takes this workers' fatigue into consideration, so as to minimize the mean flowtime of jobs.
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