• Industrial Engineering and Management Systems
• /
• 제15권2호
• /
• pp.156-172
• /
• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권5호
• /
• pp.1569-1586
• /
• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• 경영과학
• /
• 제8권1호
• /
• pp.91-108
• /
• 1991

This paper presents an efficient optimization algorithm for the crude oil tanker scheduling problem. The algorithm consists of two stages. In stage one, all the potentially optimal schedules (called 'candidate schedules') are generated from feasible schedules for each ship. In the second stage, a multiple ship scheduling problem is formulated as 0-1 integer programming problem considering only the those candidate schedules. The efficiency of the suggested algorithm was improved by exploiting the special structure of the formulation. The algorithm was illustrated by a numerical example and tested on practical ship scheduling problems.

• Journal of Communications and Networks
• /
• 제13권1호
• /
• pp.26-31
• /
• 2011

In this paper, we formulate the minimum power multicast problem in wireless networks as a mixed integer linear programming problem and then propose a Lagrangean relaxation based algorithm to solve this problem. By leveraging on the information from the Lagrangean multiplier, we could construct more power efficient routing paths. Numerical results demonstrate that the proposed approach outperforms the existing approaches for broadcast, multicast, and unicast communications.

• 충청수학회지
• /
• 제37권1호
• /
• pp.41-55
• /
• 2024

The nonconvex and nonsmooth optimization problem has been widely applicable in image processing and machine learning. In this paper, we propose an extension of the proximal iteratively reweighted ℓ₁ algorithm for nonconvex and nonsmooth minmization problem. We assume the co-coerciveness of a term of objective function instead of Lipschitz gradient condition, which is generalized property of Lipschitz continuity. We prove the global convergence of the proposed algorithm. Numerical results show that the proposed algorithm converges faster than original proximal iteratively reweighed algorithm and existing algorithms.

• 정보관리학회지
• /
• 제18권3호
• /
• pp.29-40
• /
• 2001

본 논문에서는 역색인 파일을 미용하여 학장 불리언 질의를 처리할 때 최소 비용의 질의 처리 방법을 구해 주는 질의 최적화 알고리즘을 제시한다. 확장 불리언 질의를 처리하는 방법은 질의를 구성하는 키위드의 처리 순서에 따라 여러 가지가 있을 수 있으므로 확장 불리언 질의 최적화 문제는 결국 최적 키워드 처리 순서를 구하는 문제로 귀결된다. 본 논문에서는 이 문제가 데이터베이스 질의 최적화에서 최적 조인 순서를 구하는 문제와 구조적으로 유사함을 보이고 이 분야의 연구 결과를 이용하여 문제를 해결한다. 즉, 확장 불리언 질의 처리에 대한 비용 모델을 수립하고 키워드 선택률과 역색인 파일 접근 비용을 이용하여 키워드 순위 개념을 도입한 후 이를 이용하여 최적 키워드 처리 순서를 구하는 알고리즘을 도출한다. 그리고 도출한 질의 최적화 알고리즘의 최적성을 증명하고. 실험을 통하여 실제로 최소비용의 질의 처리 방법을 구함을 보이고, 질의 최적화를 하지 않을 경우와 비교하였을 때 그 성능이 월등히 우수함을 보인다. 본 논문에서 제시한 질의 최적화 알고리즘은 정보검색시스템의 질의 처리 성능 향상에 큰 기여를 하리라 믿는다.

• Journal of applied mathematics & informatics
• /
• 제20권1_2호
• /
• pp.209-224
• /
• 2006

This paper presents an optimization model with performance constraints for two kinds of graph elements layout problem. The layout problem is partitioned into finite subproblems by using graph theory and group theory, such that each subproblem overcomes its on-off nature about optimal variable. Furthermore each subproblem is relaxed and the continuity about optimal variable doesn't change. We construct a min-max problem which is locally equivalent to the relaxed subproblem and develop the first order necessary and sufficient conditions for the relaxed subproblem by virtue of the min-max problem and the theories of convex analysis and nonsmooth optimization. The global optimal solution can be obtained through the first order optimality conditions.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 춘계학술대회논문집B
• /
• pp.144-147
• /
• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• International Journal of Quality Innovation
• /
• 제5권1호
• /
• pp.43-51
• /
• 2004

During process design or process optimization, it is quite common for experimenters to find optimum operating conditions for several responses simultaneously. The traditional multiresponse surfaces optimization methods do not consider the uncertain relationship among these responses sufficiently. For this reason, the authors propose an optimization method based on evidential reasoning theory by Dempster and Shafer. By maximizing the basic probability assignment function, which indicates the degree of belief that certain operating condition is the solution of this multiresponse surfaces optimization problem, the desirable operating condition can be found.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2000년도 추계학술발표논문집 (하)
• /
• pp.1079-1082
• /
• 2000

인터넷에서 호스트의 이동성을 지원해주기 위한 프로토콜인 Mobile IP 의 가장 근 문제점의 하나는 Triangle Routing Problem이며 이를 해결하기 위한 방안으로서 Route Optimization이 있다. 그러나, 이 방식은 Route Optimization 을 위해서 기존의 인터넷 호스트, 즉 Correspondent Node 가 Binding Cache를 유지하고, Encapsulation의 기능을 가져야 하고, Home Agent와 Security Association을 갖도록 변경이 불가피하다. 본 논문에서는 기존 인터넷 호스트에서의 변경을 필요로 하지 않는 새로운 Route Optimization 방안인 Backward-Compatible Route Optimization을 제시한다.