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In this paper, a simulation-based performance evaluation of shuttle-based storage and retrieval system (SBS/RS) is presented. In comparison with well-known automated storage and retrieval systems, SBS/RSs can substantially increase the throughput capacity of the system. The objective of this study is to exploit the benefits of SBS/RS system design for reducing the mean cycle time of transactions and consequently increasing the throughput capacity of the system. Performance comparison of the studied SBS/RS is contrasted with alternative storage rack configurations, velocity profiles of the shuttle carriers and velocity profiles of the elevators’ lifting tables in the system. The results show that SBS/RSs are effective in reducing the mean cycle time and also show large improvement by increasing throughput capacity. (Received in January 2014, accepted in October 2014. This paper was with the authors 3 months for 2 revisions.)

With the size and complexity of simulation applications growing rapidly, many simulation systems cannot be structured hierarchically, involving the interaction and dependence of elements in a hierarchy. To give an efficient credibility evaluation for the intricate simulation systems involving network configuration, this paper proposes a modified fuzzy ANP method to calculate weights of indices for assessing. The method used triangle fuzzy numbers to establish judgment matrix, together with confidence level, expressing Subject Matter Experts’ degree of understanding with respect to the importance of each component. Furthermore, a new possibility measurement for fuzzy numbers is proposed, to obtain the relative importance ranking of components for the simplified judgment in dealing with the vagueness defined measurement scales. The approach is used to calculate the credibility of a control and guide simulation system for a type of missile. The application result shows that the method is reasonable, easy and feasible. (Received in January 2010, accepted in October 2010. This paper was with the authors 1 month for 1 revision.)

In this paper a new Product Model (PM) for production is presented. An agent able to negotiate the operations that the product must undergo on the stations in manufacturing is attached to it. That agent has all the necessary information concerning its manufacturing range, the environment of production, the objectives, and the constraints and rules of production. The PM was introduced into a common experimental platform developed by the partners of the “Synchronous Production Amongst Clients and Subcontractors” (SPACS) Project. The latter integrates all the elements necessary for the management of the production in interaction with the Electronic Data Interchanges (EDI) amongst clients and subcontractors. A new approach for manufacturing systems’ control, allowing increased reactivity and flexibility, is also proposed. It is based on a social approach with a totally decentralized architecture. The manufacturing system (MS) is made up of a set of autonomous and intelligent agents as in a society. The product is considered as an actor who takes part in the decisions. The products are likened to customers and the resources to service providers. (Received in September 2006, accepted in March 2007. This paper was with the authors 2 months for 1 revision.)

A systematic procedure for modeling, simulation and optimal tuning the parameters of a Thyristor Controlled Series Compensator (TCSC) controller, for the power system stability enhancement is presented in this paper. For the simulation purpose, the model of singlemachine infinite bus (SMIB) power system with TCSC controller is developed in MATLAB/SIMULINK. The design problem of TCSC controller is formulated as an optimisation problem and genetic algorithm (GA) is employed to search for the optimal TCSC controller parameters. By minimizing a time-domain based objective function, in which the oscillatory rotor speed deviation of the generator is involved; stability performance of the power system is improved. The results obtained from simulations validate the effectiveness of proposed modelling and tuning approach for power system stability improvement. The simulation results also show that the proposed TCSC controller is effective in damping a range of small disturbance conditions in the power system. (Received in October 2006, accepted in February 2007. This paper was with the authors 1 month for 1 revision.)

This paper considers the dynamic modelling and simulation of an underactuated Remotely Operated Vehicle (ROV) designed by Robotic Research Centre (RRC), in Nanyang Technological University (NTU) using a ROV Design and Analysis (RDA) toolbox written in MATLAB/SIMULINK™. The proposed RDA provides a means to simulate the mathematical models of ROV and the control system design before planning for final hardware implementation. This is especially useful, as the ROV model is highly uncertain due to the hydrodynamic forces that are nonlinear and coupled. However, there is no commercial software for ROV control system design and analysis. (Received in May 2006, accepted in August 2006. This paper was with the authors 1 month for 1 revision.)

In this paper, a Multi-Criteria Scheduling Algorithm (MCSA) based on swapping of dispatching rules and Selective Rerouting (SR) approach based on lateral entry of critical jobs in the queue of alternate machine is used. Further, the effect of simultaneous application of MCSA and SR has been investigated. The system performance has been evaluated using mean flow time, maximum flow time, mean tardiness and maximum tardiness as the performance measures. Simulation studies using ProModel ® simulation software were carried out at different breakdown levels for a range of part complexity and part mix, in three types of flexible job shops with Job/Machine ratio less than, equal to and greater than unity involving a total of 799 simulation runs. Each run of simulation spans for a period of 2000 completed jobs. The results establish that simultaneous application of MCSA and SR improves the system performance between 12.17 % to 28.73 % and 30.51 % to 47.67 % over that when SR and MCSA respectively are applied individually. The improvement is more at low breakdown levels and high part complexity.

This work presents an algorithm for design of cellular manufacturing system. It considers sequence of operation for every component as ordinal level data. The ratio level data includes operation time per unit, production volume and machine capacity. A matrix model is developed to incorporate ordinal level data and ratio level data. Model is then standardized. From this, Part – Part correlation model is formed. This is undergone through principle component analysis. Now, Feature-Vector and New Standardized Sequence Part Load matrices are formed. These are used for grouping purpose. Part-machine orthographic view is used for concurrent part-machine family formation. Performance of algorithm is comparable and of good quality with existing methods in its class. To facilitate industrial application, it can be implemented by using free software, Scilab and/or commercial softwares. (Received in November 2008, accepted in June 2009. This paper was with the authors 1 month for 1 revision.)

The competitiveness of retail stores depends heavily on the ability to handle the challenges of reducing control costs and increasing customer service levels. One element that affects cost significantly is labour costs. This paper addresses proposing a procedure of finding the optimal solutions of personnel planning, especially by making use of the actual Point of Sales (POS) data and considering several frequency patterns of customers entering a store. First, a simulation model of the payment process is designed to establish the conditions for an integer programming (IP) model. Second, this study proposes the IP model to find the initial optimal patterns of salesclerk allocation; that is, the allocation pattern is optimal at each interval. Finally, the simulation model is used to examine the service level. With the assistance of the simulation result, the optimal solution can be obtained to satisfy a predefined service level by repeating the simulation model.

Agents are autonomous and computational entities that perceive their environment through sensors and act upon their environment through effectors. Application of agents in simulation of manufacturing system helps in modelling the concurrent behaving entities close to the real system. A manufacturing agent should be modelled to impart the required functionality to the manufacturing entity. As agents are autonomous, they run asynchronously and need to be synchronized with the simulation clock for simulating the manufacturing system. This paper deals with the synchronization of manufacturing agents, working of the agent-based simulator of a shop floor controller for a sample manufacturing system and the hybrid communication protocols involved during simulation. The manufacturing agents were built on JADE™ platform, which is a leading multi agent development framework that helps in developing FIPA compliant agent-based systems. Agent-based modelling and simulation of entities in the manufacturing system provides flexibility for real-time decision making.

Simulation software enables to build and process FMS models to analyse different aspects of the system operation. Such models, verified in simulation experiments, are ready to be used for FMS control to calculate control decisions. The idea of using simulation software Arena to control FMS is presented in the paper. Basic characteristic of modelling and simulation in Arena is presented. Arena real time module, which enables communication with external applications when the model is processed, is characterized. Required configuration options for Arena and the model are presented. To integrate Arena with local controllers of the FMS a computer program is designed. The proposed solution is implemented and verified for a real system.

In this paper we address the problem of automatically computing a set of views over a simulated three dimensional environment. The viewing system aims at, for each moment, supplying the user with the most pertinent information in order to allow a good understanding of the evolving environment. Our approach relies on an innovative optimization architecture that enables intelligent optimization techniques based on simulated annealing and genetic algorithms. Reported experiments were performed in urban rescue scenarios from the RoboCup Rescue Domain. We outline the possible extension of the proposed architecture to other visualization problems and argue on how several problems within the fields of Visualization and Rendering can benefit from it.

In this paper, the design and evaluation of the multi-aisle automated storage and retrieval systems (AS/RS) is presented. In comparison with the well known single-aisle systems, the multi-aisle systems, where the storage and retrieval machine serves more than one picking aisle, can substantially reduce the investment cost. The objective of this study is to exploit the benefits of the class-based multi-aisle system for reducing the average travel time for a transaction and consequently to increase the throughput capacity. For the storage operation, the random location assignment policy was applied, while for the retrieval operation the "first come first served" and "nearest neighbour" request selection rules were applied. The performance comparison of the single-class and class-based multi-aisle systems is contrasted with the alternative combination of the storage rack configuration and the number of picking aisles. The results show that class-based multi-aisle systems are effective in reducing the average travel time and also show large improvements in throughput capacities.