• Title/Summary/Keyword: Production and Distribution

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혼성 유전알고리듬을 이용한 단일기간 재고품목의 통합 생산-분배계획 해법 (Integrated Production-Distribution Planning for Single-Period Inventory Products Using a Hybrid Genetic Algorithm)

  • 박양병
    • 산업공학
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    • 제16권3호
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    • pp.280-290
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    • 2003
  • Many firms are trying to optimize their production and distribution functions separately, but possible savings by this approach may be limited. Nowadays, it is more important to analyze these two functions simultaneously by trading off the costs associated with the whole. In this paper, I treat a production and distribution planning problem for single-period inventory products comprised of a single production facility and multiple customers, with the aim of optimally coordinating important and interrelated decisions of production sequencing and vehicle routing. Then, I propose a hybrid genetic algorithm incorporating several local optimization techniques, HGAP, for integrated production-distribution planning. Computational results on test problems show that HGAP is effective and generates substantial cost savings over Hurter and Buer's decoupled planning approach in which vehicle routing is first developed and a production sequence is consequently derived. Especially, HGAP performs better on the problems where customers are dispersed with multi-item demand than on the problems where customers are divided into several zones based on single-item demand.

지능형 통합 생산 물류 시스템의 동기화된 시스템 설계 (A Synchronous System Design of an Intelligent-Integrated Production & Logistics Systems)

  • 배재호;왕지남
    • 산업공학
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    • 제12권2호
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    • pp.222-236
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    • 1999
  • This paper presents a design and implementation of an intelligent-integrated production-logistics systems. The situation considered here is that there are multiple manufacturing plants and multiple distribution centers. Effective distribution resource and production planning are required to reduce inventory cost and to avoid inventory shortage. We propose an intelligent forecasting scheme of each distribution centers, adaptive inventory replenishment planning, distribution resource planning, and integrated production planning system. In forecasting a huge number of on-line model identification is performed using neural network approximation capability. An efficient adaptive replenishment planning and distribution resource planning are also presented in connection with forecasting scheme. An appropriate production is also requested based on production lead-time and the results of distribution planning. Experimental simulations are presented to verify the proposed approach using real data.

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통합 공급체인관리를 위한 생산/배송 스케줄링 (Production/Distribution Scheduling for Integrated Supply Chain Management)

  • 박양병
    • 대한산업공학회지
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    • 제28권4호
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    • pp.443-453
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    • 2002
  • Many firms are trying to optimize their production and distribution systems separately, but possible profit increase by this approach is limited. Nowadays, it is more important to analyze these two systems simultaneously for the integrated supply chain management. This paper is a computational study to investigate the effectiveness of integrating production and distribution scheduling. We are interested in a multi-plant, multi-retailer, multi-product and multi-period industrial problem where the objective in solving production and distribution scheduling problem is to maximize the total net profit. Computational results on test problems of various sizes using the heuristic we developed show a substantial advantage of the integrated scheduling approach over the decoupled scheduling process. Sensitivity analysis on the parameter values indicates that, under the right conditions, the effectiveness of integrating production and distribution functions can be extremely high.

시뮬레이션과 수리모델을 이용한 생산-분배 계획 (A HYBRID SIMULATION- ANALYTIC METHOD FOR PRODUCTION-DISTRIBUTION PLANNING)

  • 김숙한;이영해
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 2000년도 춘계학술대회 논문집
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    • pp.57-66
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    • 2000
  • Production-distribution planning is the most important part in supply chain management (SCM). To solve this planning problem, either analytic or simulation approach has been developed. However these two approaches have their own demerits in problem solving. In this paper, we propose a hybrid approach which is a specific problem solving procedure combining analytic and simulation method to solve production-distribution problems in supply chain. The machine capacity and distribution capacity constraints in the analytic model are considered as stochastic factors and adjusted by the proposed specific process according to the results from independently developed simulation model which includes general production-distribution characteristics.

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공급사슬네트워크에서 시뮬레이션과 유전알고리즘을 이용한 통합생산분배계획에 대한 연구 (Study of Integrated Production-Distribution Planning Using Simulation and Genetic Algorithm in Supply Chain Network)

  • 임석진
    • 대한안전경영과학회지
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    • 제22권4호
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    • pp.65-74
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    • 2020
  • Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

친환경 쌀의 유통 특성 및 재배유형별 경영성과 분석 (Analysis of Economic Effects and Distribution Structure for Environment-friendly Rice's Production)

  • 정만철
    • 한국유기농업학회지
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    • 제15권1호
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    • pp.43-58
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    • 2007
  • This study was carried out to present the measures for the stable environment-friendly rice's production, farm income increase and consumption revitalization and so on by analyzing economic effects of the environment-friendly rice's production complex by certification type, cultivation type and distribution type. Data were collected from the environment-friendly rice's production complex in Kyunggi, Kangwon, Chungnam and Chunnam provinces. Survey was conducted with sorted by organic and no-pesticide farming. Of the samples 5 types of organic farming and 4 types of no-pesticide farming were surveyed in 17 and 18 complex, respectively. The farmers income of organic and no-pesticide farming per 10a were individually about $29{\sim}68%$ and 50% higher than the conventional farming. Base on the above results, the reasonable measures fur the stable environment-friendly rice's production and distribution and consumption revitalization were to secure partnership among business, universities, government and research institutes sectors, to organize farmers group and production complex, to establish RPC for environment-friendly rice and to introduce certification system for the distribution dealers.

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다수목표(多數目標)를 고려(考慮)한 생산(生産)-수송문제(輸送問題)에 관한 연구(硏究) (The Production-Distribution Problem with Multiple Objectives)

  • 강인선;윤덕균
    • 품질경영학회지
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    • 제19권1호
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    • pp.95-102
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    • 1991
  • This paper is concerned with the production-distribution problem with multiple conflicting objectives. In reality business firms should take account not only of the profit maximization but of various environmental criteria, namely customer services, in order to improve the business logistics. A production-distribution model of goal porgramming type considering the lead time and distribution cost by products is constructed, the solution algorithm is developed, which is based on the Ignizio's method. A numerical example is given to demonstrate the applicability of goal programming for production-distribution problem.

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환경서비스업과 물류서비스업의 예측 및 인과성 검정 (Prediction and Causality Examination of the Environment Service Industry and Distribution Service Industry)

  • 선일석;이충효
    • 유통과학연구
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    • 제12권6호
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    • pp.49-57
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    • 2014
  • Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

감마분포 공정을 위한 변동계수 관리도의 통계적 설계 (The Statistical Design of CV Control Charts for the Gamma Distribution Processes)

  • 이동원;백재원;강창욱
    • 산업경영시스템학회지
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    • 제29권2호
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    • pp.97-103
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    • 2006
  • Recently, the control chart is developed for monitoring processes with normal short production runs by the coefficient of variation(CV) characteristic for a normal distribution. This control chart does not work well in non-normal short production runs. And most of industrial processes are known to follow the non-normal distribution. Therefore, the control chart is required to be developed for monitoring the processes with non-normal short production runs by the CV characteristics for a non-normal distribution. In this paper, we suggest the control chart for monitoring the processes with a gamma short runs by the CV characteristics for a gamma distribution. This control chart is denoted by the gamma CV control chart. Futhermore evaluated the performance of the gamma CV control chart by average run length(ARL).

생산설비의 유지보수서비스와 제품의 불량률을 고려한 최적 생산주기 연구 (Determining an Optimal Production Time for EPQ Model with Preventive Maintenance and Defective Rate)

  • 김미경;박민재
    • 품질경영학회지
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    • 제47권1호
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    • pp.87-96
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    • 2019
  • Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.