• Journal of the Korean Society for Railway
• /
• v.20 no.1
• /
• pp.142-155
• /
• 2017

It is anticipated that, in cases in which different train operators share railway network, conflicts may occur among train operators with regard to train operation rate, train priorities, and arrival and departure time; besides this, during times when there is high demand for trains, operators will request train operations intensively, steadily increasing train conflict phenomena. In the present study, train operation sequence, minimum headway, arrival and departure time, train priorities, etc., were analyzed, and while using train departure times as decision variables in variably given train schedules, by adjusting train time requested by train operators, and finally rejecting the train times in cases in which conflict resolution is impossible, so that various constraints can be satisfied, a train slot allocation model was suggested to find the objective function, that is, the maximum number of train slots that can be practically applicable to railway operation.

• Journal of Intelligence and Information Systems
• /
• v.13 no.3
• /
• pp.101-117
• /
• 2007

In this paper, we propose a customized genetic algorithm (GA) to find the minimum-cost guideway network (GN) of personal rapid transit (PRT) subject to connectivity, reliability, and traffic capacity constraints. PRT is a novel transportation concept, where a number of automated taxi-sized vehicles run on an elevated GN. One of the most important problems regarding PRT is how to design its GN topology for given station locations and the associated inter-station traffic demands. We model the GN as a directed graph, where its cost, connectivity, reliability, and node traffics are formulated. Based on this formulation, we develop the GA with special genetic operators well suited for the GN design problem. Such operators include steady state selection, repair algorithm, and directed mutation. We perform numerical experiments to determine the adequate GA parameters and compare its performance to other optimization algorithms previously reported. The experimental results verify the effectiveness and efficiency of the proposed approach for the GN design problem having up to 210 links.

• Industrial Engineering and Management Systems
• /
• v.7 no.2
• /
• pp.171-181
• /
• 2008

Home care, known also as domiciliary care, is part of the community care service that is a responsibility of the local government authorities in the UK as well as many other countries around the world. The aim is to provide the care and support needed to assist people, particularly older people, people with physical or learning disabilities and people who need assistance due to illness to live as independently as possible in their own homes. It is performed primarily by care workers visiting clients' homes where they provide help with daily activities. This paper is concerned with the dispatching of care workers to clients in an efficient manner. The optimized routine for each care worker determines a schedule to achieve the minimum total cost (in terms of distance traveled) without violating the capacity and time window constraints. A collaborative population-based meta-heuristic called Particle Swarm Optimization (PSO) is applied to solve the problem. A particle is defined as a multi-dimensional point in space which represents the corresponding schedule for care workers and their clients. Each dimension of a particle represents a care activity and the corresponding, allocated care worker. The continuous position value of each dimension determines the care worker to be assigned and also the assignment priority. A heuristic assignment scheme is specially designed to transform the continuous position value to the discrete job schedule. This job schedule represents the potential feasible solution to the problem. The Earliest Start Time Priority with Minimum Distance Assignment (ESTPMDA) technique is developed for generating an initial solution which guides the search direction of the particle. Local improvement procedures (LIP), insertion and swap, are embedded in the PSO algorithm in order to further improve the quality of the solution. The proposed methodology is implemented, tested, and compared with existing solutions for some 'real' problem instances.

• Journal of Intelligence and Information Systems
• /
• v.15 no.1
• /
• pp.1-14
• /
• 2009

The Capacitated Vehicle Routing Problem (CVRP) is the problem that the vehicles stationed at central depot are to be optimally routed to supply customers with demands, satisfying vehicle capacity constraints. The CVRP is the NP-hard as it is a natural generalization of the Traveling Salesman Problem (TSP). In this article, we propose the heuristic algorithm, called the bisection seed detection method, to solve the CVRP. The algorithm is composed of 3-phases. In the first phase, we work out the initial cluster using the improved sweep algorithm. In the next phase, we choose a seed node in each initial cluster by using the bisection seed detection method, and we compose the rout with the nearest node from each seed. At this phase, we compute the regret value to decide the list of priorities for the node assignment. In the final phase, we improve the route result by using the tabu search and exchange algorithm. We compared our heuristic with different heuristics such as the Clark-Wright heuristic and the genetic algorithm. The result of proposed heuristic show that our algorithm can get the nearest optimal value within the shortest execution time comparatively.

• The KIPS Transactions:PartB
• /
• v.17B no.5
• /
• pp.389-398
• /
• 2010

The Vehicle Routing and Scheduling Problem with Time Windows(VRSPTW) is to establish a delivery route of minimum cost satisfying the time constraints and capacity demands of many customers. The VRSPTW takes a long time to generate a solution because this is a NP-hard problem. To generate the nearest optimal solution within a reasonable time, we propose the heuristic by using an ACO(Ant Colony Optimization) with multi-cost functions. The multi-cost functions can generate a feasible initial-route by applying various weight values, such as distance, demand, angle and time window, to the cost factors when each ant evaluates the cost to move to the next customer node. Our experimental results show that our heuristic can generate the nearest optimal solution more efficiently than Solomon I1 heuristic or Hybrid heuristic applied by the opportunity time.

• Korean Management Science Review
• /
• v.32 no.4
• /
• pp.109-133
• /
• 2015

This paper considers the allocation and engagement scheduling of air defense missiles by using MIP (mixed integer programming). Specifically, it focuses on developing a realistic MIP model for a real battle situation where multiple enemy missiles are headed toward valuable defended assets and there exist multiple air defense missiles to counteract the threats. In addition to the conventional objective such as the minimization of surviving target value, the maximization of total intercept altitude is introduced as a new objective. The intercept altitude of incoming missiles is important in order to minimize damages from debris of the intercepted missiles and moreover it can be critical if the enemy warhead contains an atomic or chemical bomb. The concept of so called the time window is used to model the engagement situation and a continuous time is assumed for flying times of the both missiles. Lastly, the model is extended to simulate the situation where the guidance radar, which guides a defense missile to its target, has the maximum guidance capacity. The initial mathematical model developed contains several non-linear constraints and a non-linear objective function. Hence, the linearization of those terms is performed before it is solved by a commercially available software. Then to thoroughly examine the MIP model, the model is empirically evaluated with several test problems. Specifically, the models with different objective functions are compared and several battle scenarios are generated to evaluate performance of the models including the extended one. The results indicate that the new model consistently presents better and more realistic results than the compared models.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.5
• /
• pp.1921-1929
• /
• 2015

The smart substation is the heart of a transmission system, which is particularly emphasized as the most significant composition of smart grids in China. In order to assess the functionality performance of substation technologies, this paper presents methods used to identify the most promising solutions for smart substation design and to evaluate the technical levels of available technologies. The multi-index optimization model is presented to address the issue of smart substation planning. A mathematical model of the planning decision problem is established with multiple objectives consisting of economic, reliability, and green key indices, and many kinds of concerns including physical and environmentally friendly operations are formulated as a set of constraints. With respect to the assessment of the technical level regarding integration of advanced technologies into a substation, a modified grey whitenization weight function is adopted to structure a novel grey clustering method. The proposed grey clustering approach is used to overcome the difficulty of insufficient quantitative assessment capacity for traditional methods. The evaluation of technical effects provides the classification definition for the development phase and the maturity level of the smart substation. The effectiveness of the proposed approaches in planning decision-making and evaluation of construction efforts is demonstrated with case studies involving the actual smart substation projects of Wenchongkou substation in China Southern Power Grid (CSG) and Mengzi substation in State Grid Corporation of China (SGCC).

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.44 no.11
• /
• pp.973-980
• /
• 2016

An air traffic management (ATM) has been studied in a variety of fields to utilize an air traffic capacity efficiently and solve a congested air traffic situation due to an increment of an air traffic demand. In this paper, an air traffic management, which is related with controlling and determining the sequencing of an aircraft approaching to an airport, in terminal control area is studied. This paper focuses on scheduling algorithms with a given problem for the air traffic management with operational constraints, such as a space separation, an overtaking on the same air-route, and a route merge point (a scheduling point). For a real-time calculation, the presented algorithms focus on dispatching heuristic rules which are able to assign tasks in a fast time period with an adequate performance, which can be demonstrated as a proper and realistic scheduling algorithm. A simulation result is presented to illustrate the validity and applicability of the proposed algorithm. Each scheduling rule is analyzed on the same static and dynamic air traffic flow scenario with the ATM Monte-Carlo simulation.

• Structural Engineering and Mechanics
• /
• v.62 no.5
• /
• pp.619-629
• /
• 2017

This paper focuses on the study of complete dynamic modeling and maximum dynamic load carrying capacity computation of N-flexible links and N-flexible joints mobile manipulator undergoing large deformation. Nonlinear dynamic analysis relies on the Timoshenko theory of beams. In order to model the system completely and precisely, structural and joint flexibility, nonlinear strain-displacement relationship, payload, and non-holonomic constraints will be considered to. A finite element solution method based on mixed method is applied to model the shear deformation. This procedure is considerably more involved than displacement based element and shear deformation can be readily included without inducing the shear locking in the element. Another goal of this paper is to present a computational procedure for determination of the maximum dynamic load of geometrically nonlinear manipulators with structural and joint flexibility. An effective measure named as Moment-Height Stability (MHS) measure is applied to consider the dynamic stability of a wheeled mobile manipulator. Simulations are performed for mobile base manipulator with two flexible links and joints. The results represent that dynamic stability constraint is sensitive when calculating the maximum carrying load. Furthermore, by changing the trajectory of end effector, allowable load also changes. The effect of torsional spring parameter on the joint deformation is investigated in a parametric sensitivity study. The findings show that, by the increase of torsional stiffness, the behavior of system approaches to a system with rigid joints and allowable load of robot is also enhanced. A comparison is also made between the results obtained from small and large deformation models. Fluctuation range in obtained figures for angular displacement of links and end effector path is bigger for large deformation model. Experimental results are also provided to validate the theoretical model and these have good agreement with the simulated results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.24 no.4
• /
• pp.95-102
• /
• 2010

As the electric power industry is evolving into competitive market scheme, a new paradigm is required for the operation of market. Traditional dispatch algorithm was built based on the optimization model with an objective function and multiple constraints. Commercial market simulator followed the concept of the microeconomic model used in the dispatch algorithm, which is called as analytic method. On analytic method it is prerequisite to procure the exact data for the simulation. It is not easy anymore for each market participant to access to other participants' financial information while it used to be easy for monopoly decision maker to know all the information needed for the optimal operation. Considering the changing situation, it is required to introduce a new method for estimating the market price. This paper proposes an empirical method based on stochastic processes expected to build a capacity planning and long term contracts.