• Asia pacific journal of information systems
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• v.27 no.1
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• pp.1-17
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• 2017

The need for effective information systems that can help in efficient transportation management has become essential. This study presents the potential benefits of developing a decision support system used by a trucking company for routing and scheduling. Our study investigates how customer exibility factors affect the utilization of transportation resources and establishes a vehicle scheduling model for better allocation of transportation resources with a time window. The results show vehicle savings from 25% up to 70% per day given different levels of exibility in delivery times. Increased capacity utilization can be achieved by considering only customer exibility in the model. Our study implies that incorporating customer exibility into the information system can help transportation organizations have the capability to gain control over management to cut costs and improve service.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.646-655
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• 2008

A main issue about production management of shipyards is to efficiently manage the work in process and logistics. However, so far the management of a transporter for moving building blocks has not been efficiently performed. To solve the issues, optimal block transporting scheduling system is developed for minimizing of the travel distance without overload of a transporter. To implement the developed system, a hybrid optimization algorithm for an optimal block transportation scheduling is proposed by combining the genetic algorithm and the ant algorithm. Finally, to evaluate the applicability of the developed system, it is applied to a block transportation scheduling problem of shipyards. The result shows that the developed system can generate the optimal block transportation scheduling of a transporter which minimizes the travel distance without overload of the transporter.

• IE interfaces
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• v.20 no.4
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• pp.525-538
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• 2007

The importance of efficient container transportation becomes more significant each year due to the constant growth of the global marketplace, and studies focusing on shipping efficiency are becoming increasingly important. In this paper, we propose an approach for vehicle scheduling that decreases the number of vehicles required for freight commerce by analyzing and scheduling optimal routes. Container transportation can be classified into round and single-trip transportation, and each vehicle can be linked in a specific order based on the vehicle state after completing an order. We develop a mathematical model to determine the required number of vehicles with optimal routing, and a heuristic algorithm to perform vehicle scheduling for many orders in a significantly shorter duration. Finally, we tested some numerical examples and compared the developed model and the heuristic algorithm. We also developed a decision support system that can schedule vehicles based on the heuristic algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.129-139
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• 2016

This paper presented a robust ship scheduling model using the quadratic programming problem. Given a set of available carriers under control and a set of cargoes to be transported from origin to destination, a robust ship scheduling that can minimize the mean-variance objective function with the required level of profit can be modeled. Computational experiments concerning relevant maritime transportation problems are performed on randomly generated configurations of tanker scheduling in bulk trade. In the first stage, the optimal transportation problem to achieve maximum revenue is solved through the traditional set-packing model that includes all feasible schedules for each carrier. In the second stage, the robust ship scheduling problem is formulated as mentioned in the quadratic programming. Single index model is used to efficiently calculate the variance-covariance matrix of objective function. Significant results are reported to validate that the proposed model can be utilized in the decision problem of ship scheduling after considering robustness and the required level of profit.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• IE interfaces
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• v.22 no.1
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• pp.63-72
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• 2009

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition, cancellation or change of block transportation requirements, sudden breakdowns and maintenance of transporters. The transportation of the blocks in the shipyard has some distinct characteristics. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times: 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after the required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose a heuristic algorithm based on a network flow model which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Also, a rolling-horizon scheduling method is proposed for dynamic block transportation environment. The performance of the proposed heuristic algorithms are evaluated through a simulation experiment.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Journal of Navigation and Port Research
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• v.30 no.7
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• pp.561-566
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• 2006

In this paper, we propose a new ship scheduling set packing model considering limited risk or variance. The set packing model is used in many applications, such as vehicle routing, crew scheduling, ship scheduling, cutting stock and so on. As long as the ship scheduling is concerned, there exits many unknown external factors such as machine breakdown, climate change and transportation cost fluctuation. However, existing ship scheduling models have not considered those factors apparently. We use a quadratic set packing model to limit the variance of expected cost of ship scheduling problems under stochastic spot rates. Set problems are NP-complete, and additional quadratic constraint makes the problems much harder. We implement Kelley's cutting plane method to replace the hard quadratic constraint by many linear constrains and use branch-and-bound algorithm to get the optimal integral solution. Some meaningful computational results and comments are provided.

• IE interfaces
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• v.21 no.3
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• pp.274-282
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• 2008

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition or cancellation of block transportation requirements, sudden breakdowns and maintenance of transporters. The transportation of the blocks in the shipyard has some distinct characteristics. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times : 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after the required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose heuristic algorithms which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Four heuristic algorithms for transporter scheduling are proposed and their performance is evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.574-581
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• 2001

In this paper we design and evaluate the longitudinal nonlinear N(aub)z-CSAS(Command and Stability Augmentation System) flight control law in \"DMI(Dynamic Model Inversion)-method\" and classical \"Gain Scheduling-method\", respectively, to meet the handling quality requirements associated with push-over pull-up maneuver. It is told that the flight control law designed in \"DM-method\" is adequate to the full flight regime without gain scheduling and is efficient to produce the time response shape desired to the handling quality requirements. On the contrary, the flight control law designed in \"Gain Scheduling-method\" is easy to be implemented in flight control computer and insensitive to variation of the actuator model characteristics.n of the actuator model characteristics.