• 한국산학기술학회논문지
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• 제13권7호
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• pp.2955-2963
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• 2012

본 논문은 다품종 동적 로트사이징 문제를 풀기 위하여 열생성 기법에 기반한 알고리즘을 제안한다. 제안한 알고리즘의 기본 개념은 한정된 생산 용량을 주문제를 통하여 n개의 제품에 할당하고, 주문제에 의하여 할당된 생산용량을 기반으로 하여 각각의 제품에 대하여 최적화된 로트사이징 문제를 반복적으로 풀어나감으로써 해를 구해나가는 것이다. 부문제를 풀기 위해 본 논문은 로트사이즈, 재공재고 그리고 생산량 간에 존재하는 비선형관계를 기반으로 한 M/G/1모델 기반의 최적화 로트사이징 모델을 제안한다. 실험을 통하여 제안한 알고리즘이 비교적 짧은 시간안에 좋은 해를 생성함을 보여준다.

• International Journal of Advanced Culture Technology
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• 제8권2호
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• pp.270-276
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• 2020

In this paper, we analyze the buyer's joint pricing and lot-sizing model in a two-stage supply chain consisting of the supplier, the buyer and the customer. It is assumed that the supplier will permit a certain fixed period for settling the amount the buyer owes to him for the items supplied in order to stimulate the demand for the product. Generally, credit transactions would have a positive effect to the buyer. The availability of credit transactions from the supplier effectively reduces the cost of holding stocks for the buyer and therefore, the buyer has a lot of price options to choose his sales price for a customer in anticipation of increased the customer's demand and, as a result, it will appear to increase the buyer's inventory levels. On the other hand, in the case of decaying products in which their utility decay over time, the decaying rate with time may be expected to reduce inventory levels. In this regard, we need to analyze how much the length of credit period and the decaying rate affect the buyer's pricing and lot-sizing policy. For the analysis, we consider the situation where the customer's demand is represented as a linearly decreasing function of the buyer's sales price. From this perspective, we formulate the buyer's annual net profit and analyze the effect of the length of credit period and decaying rate of the product on the buyer's inventory policy numerically.

• 한국산학기술학회논문지
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• 제7권1호
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• pp.89-95
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• 2006

공급사슬망에서 분산되어있는 제조시스템에 대한 생산 계획수립은 공급사슬관리의 주요 연구분야 중의 하나이다. 본 논문은 공급사슬망에서 자원제약을 갖는 다단계 다품목 로트사이즈 결정 문제(Multi-Level, multi-item Capacitated Lot Sizing Problem: MLCLSP)를 위한 알고리즘을 제시한다. MLCLSP는 MIP(mixed integer program) 문제에 해당한다. 제안된 알고리즘은 휴리스틱과 최적화 패키지인 LINGO를 이용해 서로 반복적인 방식으로 해를 풀어나가는 혼성적인 성격을 갖는다. 휴리스틱을 이용하여 정수형 변수를 결정한 후, 얻게 되는 LP(linear program) 문제를 LINGO를 이용하여 해를 개선해 나가는 방식을 기본으로 한다. 본 논문에서는 탐색 휴리스틱 기법으로 임의 재시작 타부탐색 알고리즘을 제시한다. 다양한 시나리오의 실험을 통해 제안된 알고리즘들의 성능을 평가한다.

• 대한산업공학회지
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• 제40권4호
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• pp.435-441
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• 2014

This paper considers a single-product problem for inbound lot-sizing and outbound dispatching at a third-party warehouse, where the demand is dynamic over the discrete time horizon. Each demand must be delivered into the corresponding delivery time window which is the time interval characterized by the earliest and latest delivery dates of the demand. Ordered products are shipped by heterogeneous container types. Each container type has type-dependent carrying capacity and the unit freight cost depends on each container type. Total freight cost is proportional to the number of each container type used. Also it is assumed that related cost functions are concave and backlogging is not allowed. The objective of the paper is to simultaneously determine the optimal inbound lot-sizing and outbound dispatching plans that minimize total costs which include ordering, shipping, and inventory holding costs. The optimal solution properties are characterized for the problem and then a dynamic programming algorithm is presented to find the optimal solution.

• 산업공학
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• 제13권3호
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• pp.378-387
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• 2000

As the globalization of manufacturing companies continues, the scope of dependence between these companies and distributors, and other suppliers are growing very rapidly since no one company manufactures or distributes the whole product by themselves. And, the need to increase the efficiency of the whole supply chain is increasing. This paper deals with a multi-plant lot-sizing problem(MPLSP) which happens in a decentralized manufacturing system of a supply chain. In this study, we assume that the whole supply chain is driven by a single source of independent demand and many levels of dependent demands among manufacturing systems in the supply chain. We consider setup cost, transportation cost and time, and inventory holding cost as a decision factor in the MPLSP. The MPLSP is decomposed into two sub-problems: a planning problem of the whole supply chain and a lot-sizing problem of each manufacturing system. The supply chain planning problem becomes a pure linear programming problem and a Generalized Goal Decomposition method is used to solve the problem. Its result is used as a goal of the lot-sizing problem. The lot-sizing problem is solved using the CPLEX package, and then the coefficients of the planning problem are updated reflecting the lot-sizing solution. This procedure is repeated until termination criteria are met. The whole solution process is similar to Lagrangian relaxation method in the sense that the solutions are approaching the optimum in a recursive manner. Through experiments, the proposed closed-loop hierarchical planning and traditional hierarchical planning are compared to optimal solution, and it is shown that the proposed method is a very viable alternative for solving production planning problems of decentralized manufacturing systems and in other areas.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• 대한산업공학회지
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• 제40권4호
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• pp.424-427
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• 2014

In this paper, we consider a production system in which the items are produced by batch. For a production planning of the system, we formulate a lot-sizing problem in which each production should be a multiple of a given unit batch and backlogging is allowed. We propose an optimal dynamic programming algorithm for the plan whose complexity is $O(T^2)$ where T is the maximum number of periods in a plan.

• 대한산업공학회지
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• 제17권1호
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• pp.29-35
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• 1991

This paper deals with a production-inventory model for two-stage batch production system. We propose a lot-sizing scheme which combines the integer multiple lot requirements (IMLR) policy and the integer split lot requirements (ISLR) policy. An iterative search procedure for optimal decision variables is presented and numerical examples are solved to illustrate the validity of the model. The results show that the proposed scheme outperforms the existing policies.

• 제어로봇시스템학회논문지
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• 제18권9호
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• pp.854-862
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• 2012

The optimal design of batch-storage network by using periodic square wave model provides analytical lot sizing equations for a complex supply chain network characterized as multi-supplier, multi-product, multi-stage, non-serial, multi-customer, cyclic system including recycling and/or remanufacturing. The network structure includes multiple currency flows as well as material flows. The processes are represented by multiple feedstock/product materials with fixed composition which are very suitable for production processes. In this study, transportation processes that carry multiple materials with unknown composition are added and the time frame is changed from single period into multiple periods in order to represent nonperiodic parameter variations. The objective function of the optimization involves minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders in the numeraire currency. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a multiperiod subproblem for average flow rates and analytical lot-sizing equations. The multiperiod lot sizing equations are different from single period ones. The effects of corporate income taxes, interest rates and exchange rates are incorporated.

• Industrial Engineering and Management Systems
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• 제11권3호
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• pp.288-298
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• 2012

Lot sizing and shipment scheduling are two interrelated decisions made by a manufacturing plant and a third-party logistics distribution center. This paper analyzes a dynamic inbound ordering problem and shipment problem with a freight container cost, in which the order size of multiple products and single container type are simultaneously considered. In the problem, each ordered product placed in a period is immediately shipped by some freight containers in the period, and the total freight cost is proportional to the number of containers employed. It is assumed that the load size of each product is equal and backlogging is not allowed. The objective of this study is to simultaneously determine the lot-sizes and the shipment schedule that minimize the total costs, which consist of production cost, inventory holding cost, and freight cost. Because the problem is NP-hard, we propose three meta-heuristic algorithms: a simulated annealing algorithm, a genetic algorithm, and a new population-based evolutionary meta-heuristic called self-evolution algorithm. The performance of the meta-heuristic algorithms is compared with a local search heuristic proposed by the previous paper in terms of the average deviation from the optimal solution in small size problems and the average deviation from the best one among the replications of the meta-heuristic algorithms in large size problems.