• 한국철도학회논문집
• /
• 제17권4호
• /
• pp.313-319
• /
• 2014

여객 증편열차 운영은 수송력 보강이나 관광열차 운행을 위해 증편된다. 화물열차의 경우는 철도화물수요를 위해 주로 증편된다. 기존 연구들에서는 증편열차 스케줄 작성을 위해 추가 열차의 운행시각을 지정한 후에 운행가능성을 판단한다. 그러나 국내에서 이러한 방법의 경우 추가열차의 증편이 불가능한 경우가 많다. 왜냐하면 한국철도 네트워크는 운행밀도가 높고 여러 차종이 있기 때문이다. 특히 화물열차의 경우 여객열차와의 경합이 발생할 때마다 지연이 증가되거나 운행이 불가능하다. 본 논문에서는 출발시각이 지정된 요청열차 스케줄과 시간범위 내에 운행 가능한 스케줄을 찾을 수 있는 열차 증편모형을 제시한다. 제시된 모형은 혼합정수 계획법으로 모델링하고 열 생성기법을 사용하였다.

• 산업경영시스템학회지
• /
• 제42권1호
• /
• pp.143-150
• /
• 2019

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

• Management Science and Financial Engineering
• /
• 제14권2호
• /
• pp.45-66
• /
• 2008

Refuse collection, one of important elements in reverse logistics, is an activity rendering recyclables or wastes and moving them to some points where further treatment is required. Among various decisions in the collection activity, we focus on network design, which is the problem of locating collection points as well as allocating refuses at demand points to collection points while satisfying the capacity restriction at each collection point. Here, the collection point is the place where recyclables or wastes near the point are gathered, and locating the collection points is done by selecting them from a given set of potential sites. The objective is to minimize the sum of fixed costs to open collection points and transportation costs to move refuses from demand points to collection points. An integer programming model is developed to represent the problem mathematically and due to the complexity of the problem, two types of heuristics, one with simultaneous and the others with separate location and allocation, are suggested. Computational experiments were done on test problems up to 500 potential sites, and the results are reported. In particular, some heuristics gave near optimal solutions for small-size test problems, i.e., 2% gaps in average from the optimal solution values.

• 대한산업공학회지
• /
• 제38권2호
• /
• pp.116-124
• /
• 2012

This paper concerns a joint replenishment problem for a single buyer who sells multiple types of items to end-customers. The buyer periodically replenishes the inventory of each item to a preset order-up-to-level to satisfy the end customers' demands, which may be non-stationary. A joint replenishment policy characterized by variable order-up-to-levels is proposed for the buyer who wishes to minimize the expected cost of operating the retail system. The proposed policy starts each period by calculating the expected cost of ordering and not ordering action based on the information of the current inventory position and forecasted demand for the upcoming period. It then takes advantage of an integer programming model to get a cost effective joint replenishment plan. Computer experiment was performed to test efficiency of the proposed policy. When compared with the most efficient policy currently available, our policy showed a considerable cost savings especially for the problems having non-stationary demands.

• Industrial Engineering and Management Systems
• /
• 제12권4호
• /
• pp.336-350
• /
• 2013

This paper proposes a mathematical modeling-based approach for assessing disaster effects and selecting suitable mitigation alternatives to provide humanitarian relief (HR) supplies, shelter, rescue services, and long-term services after a disaster event. Mitigation steps, such as arrangement of shelter and providing HR items (food, water, medicine, etc.) are the immediate requirements after a disaster. Since governments and non-governmental organizations (NGOs) providing humanitarian aid need to know the requirements of relief supplies and resources for collecting relief supplies, organizing and initiating mitigation steps, a quick assessment of the requirements is the precondition for effective disaster management. Based on satellite images from weather forecasting channels, an area/dimension of the disaster-affected zones and the extent of the overall damage may often be obtained. The proposed approach then estimates the requirements for HR supplies, supporting resources, and rescue services using the census and other government data. It then determines reliable transportation routes, optimum collection and distribution centers, alternatives for resource support, rescue services, and long-term help needed for the disaster-affected zones. A numerical example illustrates the applicability of the model in disaster mitigation planning.

• Industrial Engineering and Management Systems
• /
• 제12권4호
• /
• pp.351-358
• /
• 2013

This paper proposes a multiobjective model describing the trade-offs involved in selecting the locations of drop-off boxes for collecting used products and transporting these products to designated locations. We assume the following reverse flow of used products. Owners of used products (cellular phones, digital cameras, ink cartridges, etc.) take them to the nearest drop-off box when the distance is reasonably short. We also assume that owners living closer to drop-off boxes dispose of more used products than do owners living farther from drop-off boxes. Different types of used products are collected, with each type requiring its own drop-off box. A transportation destination for each product is specified. Three objectives are considered: maximizing the volume of used products collected at drop-off boxes; minimizing the cost of transporting collected products to designated locations; and minimizing the cost of allocating space for drop-off boxes. We formulate the above model as a multiobjective integer programming problem and generate the corresponding set of Pareto optimal solutions. We apply the model to an area using population data for Chofu City, Tokyo, Japan, and analyze the trade-offs between the objectives.

• 한국시뮬레이션학회논문지
• /
• 제22권4호
• /
• pp.149-156
• /
• 2013

본 연구에서는 네트워크 총 비용 최소화의 관점에서 스마트 노드 자원사용과 네트워크 트래픽 경로를 함께 결정하는 최적화 문제를 고려하였다. 이를 위해, 스마트 노드의 기술 추세와 자원 최적화에 대한 분석방법, 스마트 네트워크의 경제적 효과와 CDN에 대해 살펴보았다. CDN에 대한 분석을 기반으로 혼합정수계획법 모형을 제안하였으며, 이는 기존에 알려진 복제위치선정과 고객요청 분배문제 (RPRDP)와 경로 결정문제가 결합된 형태로 볼 수 있다. 제안된 혼합정수계획법 모형을 구현하고 그 결과를 소개함으로써 제안된 모형의 유효성을 밝혔다.

• 제어로봇시스템학회논문지
• /
• 제3권2호
• /
• pp.187-196
• /
• 1997

This paper presents a semi-automatic methodology to synthesize executable digital controller saftware in a multi-loop control system. A digital controller is described by a task graph and end-to-end timing requirements. A task graph denotes the software structure of the controller, and the end-to-end requirements establish timing relationships between external inputs and outputs. Our approach translates the end-to-end requirements into a set of task attributes such as task periods and deadlines using nonlinear optimization techniques. Such attributes are essential for control engineers to implement control programs and schedule them in a control system with limited resources. In current engineering practice, human programmers manually derive those attributes in an ad hoc manner: they often resort to radical over-sampling to safely guarantee the given timing requirements, and thus render the resultant system poorly utilized. After task-specific attributes are derived, the tasks are scheduled on a single CPU and the compiled kernel is synthesized. We illustrate this process with a non-trivial servo motor control system.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.945-949
• /
• 2004

These days there are so many scheduling systems or softwares. But only few scheduling systems have succeeded in the market. In spite of powerful engine and functions, those systems have difficulties to be applied in real processes. In real processes, there are various constraints caused by physical or systematical environments of plants. Those constraints are too many to be handled in the system. This problem makes it difficult for the system to represent the details of processes. In order to resolve this problem, we have developed a specialized scheduling system for a target process. The system could be developed by the experts for target process and researchers for scheduling. In this study, a scheduling system for PVC process has been developed as an MILP (Mixed integer linear programming) model and coded in $Fortran^{TM}$. The scheduling system has been applied to two processes, which have different characteristics. Simulation results indicate that the profit of the target process can be increased by about 5% by implementing the scheduling system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권3호
• /
• pp.921-940
• /
• 2015

In this paper, we investigate the multi-resource allocation problem, a unique feature of which is that the multiple resources can compensate each other while achieving the desired system performance. In particular, power and time allocations are jointly optimized with the target of energy efficiency under the resource-limited constraints. Different from previous studies on the power-time tradeoff, we consider a multi-server case where the concurrent serving users are quantitatively restricted. Therefore user selection is investigated accompanying the resource allocation, making the power-time tradeoff occur not only between the users in the same server but also in different servers. The complex multivariate optimization problem can be modeled as a variant of 2-Dimension Bin Packing Problem (V2D-BPP), which is a joint non-linear and integer programming problem. Though we use state decomposition model to transform it into a convex optimization problem, the variables are still coupled. Therefore, we propose an Iterative Dual Optimization (IDO) algorithm to obtain its optimal solution. Simulations show that the joint multi-resource allocation algorithm outperforms two existing non-joint algorithms from the perspective of energy efficiency.