• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.78-86
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• 2010

The traveling purchaser problem(TPP) is a generalization of the well-known traveling salesman problem(TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. TPP also could be extended to the vehicle routing problem(VRP) by incorporating additional constraints such as multi-purchaser, capacity, distance and time restrictions. In the last decade, TPP has received some attention of the researchers in the operational research area. However it has not received the equivalent interest as much as TSP and VRP. Therefore, there does not exist a review of the TPP. The purpose of this paper is to review the TPP and to describe solution procedures proposed for this problem. We also introduce the ILP formulation for the multiple TPP(mTPP) which is generalized type of TPP. We compare the system performance according to change from TPP to mTPP.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.137-158
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• 1992

We study the Multiple Product Single Facility Stockout Avoidance Problem (SAP). That is the problem of determining, given initial inventories, whether there is a multiple product single facility production schedule that avoids stockouts over a given time horizon. The optimization version of the SAP where stockouts are pnelized linearly is also studied. We call this problem the Weighted Stockout Problem (WSP). Both problems are NP-hard in the strong sense. We develop Mixed Integer Linear Programming (MIP) formulations for both the SAP and the WSP. In addition, several heuristic algorithms are presented and performances are tested using computational experiments. We show that there exist polynomial algorithms for some special cases of the SAP and the WSP. We also present a method to phase into a target cyclic schedule for infinite horizon problems. These can be used as a practical scheduling tool for temporarily overloaded facilities or to reschedule production after a disruption.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.112-117
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• 2007

In this paper, we focus on the total transmission power minimization problem for downlink beamforming multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems while ensuring each user's QoS requirement. Although the linear integer programming (LIP) solution we formulate provides the performance upper bound of the margin adaptive (MA) optimization problem, it is hard to be implemented in practice due to its high computational complexity. By regarding each user's equivalent channel gain as approximate independent values and using iterative descent method, we present a heuristic MA resource allocation algorithm. Simulation results show that the proposed algorithm efficiently converges to the local optimum, which is very close to the performance of the optimal LIP solution. Compared with existing space division multiple access (SDMA) OFDM systems with or without adaptive resource allocation, the proposed algorithm achieves significant performance improvement by exploiting the frequency diversity and multi-user diversity in downlink multiple-input single-output (MISO) OFDM systems.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.1
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• pp.111-124
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• 2010

In the last decade, traveling purchaser problem (TPP) has received some attention of the researchers in the operational research area. TPP is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In this paper we suggest heterogeneous multiple traveling purchaser problem with budget constraint (HMTPP-B) which looks for several cycles starting at and ending to the depot and visiting a subset at a minimum traveling cost and such that the demand for each product is satisfied and the cost spent for purchasing the products does not exceed a given budget threshold. All the past studies of TPP are restricted on a single purchaser. Therefore we randomly generated some instances. CPLEX is used for getting optimal solutions in these experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.763-770
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• 2022

In an environment where multiple drones are operated, collisions can occur when path points overlap, and collision avoidance in preparation for this is essential. When multiple drones perform multiple tasks, it is not appropriate to use a method to generate a collision-avoiding path in the path planning phase because the path of the drone is complex and there are too many collision prediction points. In this paper, we generate a path through a commonly used path generation algorithm and propose a collision avoidance method using speed profile optimization from that path segment. The safe distance between drones was considered at the expected point of collision between paths of drones, and it was designed to assign a speed profile to the path segment. The optimization problem was defined by setting the distance between drones as variables in the flight time equation. We constructed the constraints through linearize and convexification, and compared the computation time of SQP and convex optimization method in multiple drone operating environments. Finally, we confirmed whether the results of performing convex optimization in the 20 drone operating environments were suitable for the multiple drone operating system proposed in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1373-1391
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• 2022

We investigate mobile multiple-input multiple-output (MIMO) molecular communication via diffusion (MCvD) system which is consisted of two source nodes, two destination nodes and one relay node in the mobile three-dimensional channel. First, the combinations of decode-and-forward (DF) relaying protocol and network coding (NC) scheme are implemented at relay node. The adaptive thresholds at relay node and destination nodes can be obtained by maximum a posteriori (MAP) probability detection method. Then the mathematical expressions of the average bit error probability (BEP) of this mobile MIMO MCvD system based on DF and NC scheme are derived. Furthermore, in order to minimize the average BEP, we establish the optimization problem with optimization variables which include the ratio of the number of emitted molecules at two source nodes and the initial position of relay node. We put forward an iterative scheme based on block coordinate descent algorithm which can be used to solve the optimization problem and get optimal values of the optimization variables simultaneously. Finally, the numerical results reveal that the proposed iterative method has good convergence behavior. The average BEP performance of this system can be improved by performing the joint optimizations.

• Journal of Communications and Networks
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• v.13 no.4
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• pp.327-338
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• 2011

With the incitation to reduce power consumption and the aggressive reuse of spectral resources, there is an inevitable trend towards the deployment of small-cell networks by decomposing a traditional single-tier network into a multi-tier network with very high throughput per network area. However, this cell size reduction increases the complexity of network operation and the severity of cross-tier interference. In this paper, we consider a downlink two-tier network comprising of a multiple-antenna macrocell base station and a single femtocell access point, each serving multiples users with a single antenna. In this scenario, we treat the following beamforming optimization problems: i) Total transmit power minimization problem; ii) mean-square error balancing problem; and iii) interference power minimization problem. In the presence of perfect channel state information (CSI), we formulate the optimization algorithms in a centralized manner and determine the optimal beamformers using standard convex optimization techniques. In addition, we propose semi-decentralized algorithms to overcome the drawback of centralized design by introducing the signal-to-leakage plus noise ratio criteria. Taking into account imperfect CSI for both centralized and semi-decentralized approaches, we also propose robust algorithms tailored by the worst-case design to mitigate the effect of channel uncertainty. Finally, numerical results are presented to validate our proposed algorithms.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.201-219
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• 2014

This paper considers service deployment and priority optimization for multiple service-oriented applications sharing reusable services, which are deployed as multiple instances in the cloud. In order to handle variations in the workloads of the multiple applications, service instances of the individual reusable services are dynamically provisioned in the cloud. Also service priorities for each application in a particular reusable service are dynamically adjusted. In this paper, we propose an analytic performance model, based on a queueing network model, to predict the expected sojourn times of multiple service-oriented applications, given the number of service instances and priority disciplines in individual reusable services. We also propose a simple heuristic algorithm to search an optimal number of service instances in the cloud and service priority disciplines for each application in individual reusable services. A numerical example is also presented to demonstrate the applicability of the proposed performance model and algorithm to the proposed optimal decision problem.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.36-40
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• 2023

Recently, in the problem of multi-order processing in logistics warehouses, multi-pickup systems are changing from the form in which workers walk around the warehouse to the form in which goods come to workers. These changes are shortening the time to process multiple orders and increasing production. This study considered the sequence problem of which warehouse the items to be loaded on each truck come first and which items to be loaded first when loading multiple pallet-unit goods on multiple trucks in an industrial smart logistics automation warehouse. To solve this problem efficiently, we use the mutant algorithm, which combines the GA algorithm and ACO algorithm, and compare with original system.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.777-786
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• 2007

This paper presents a modified simulated annealing algorithm to optimize linear scheduling projects with multiple resource constraints and its effectiveness is verified with a proposed problem. A two-stage solution-finding procedure is used to model the problem. Then the simulated annealing and the modified simulated annealing are compared in the same condition. The comparison results and the reasons of improvement by the modified simulated annealing are presented at the end.