• IE interfaces
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• v.16 no.3
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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.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.198-208
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• 2007

Recently business enterprises have forced to face in fierce competition in today's global markets due to the short life cycles of products and the higher expectation of customers. Together with continuing advances in communications and transportation technologies, these environments have motivated the continuous evolution of the supply chain and the management techniques. This paper consider three-echelon inventory system which consist of one manufacturer, one distributor and N retailers for a single product under assumption of constant demand. This paper propose the inventory replenishment period using heuristic method and order policy through coordination of inventory replenishment period. The simulation results show that decrease the total cost of the three-echelon inventory system.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.1
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• pp.1-10
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• 1987

This paper deals with a single-facility multiproduct lot-size model requiring consideration of setup costs. Each product is demanded at the constant rate per unit time in the next particular period. Due to the limitation of the production capacity, some productions of total demand requirement in that period must be pre-produced. The aim of this project is to determine when and how much of each product to make in order to minimize the total setup costs and inventory carrying-costs of all products. Also this paper contains the further realistic treatment of inventory carrying-costs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.36-43
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• 2013

Many retailer store managers are experiencing the situation where some customers balk at purchasing products if the stock is low. In this paper, we extend the single period newsvendor model in an environment of customer balking behavior occurring at double threshold inventory levels assuming the chance of sales during balking is a discrete function of inventory level. Our analysis is based on the assumption that only the mean and the variance of demand are known, without assuming any specific distributional form. We derive the explicit general expression of optimal order quantity with unknown distribution of demand with double threshold inventory levels of customer balking. Then, we illustrate the concepts developed here through simple numerical examples and conclude the future research topics under balking situation.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.95-102
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• 2013

It is difficult to determine an appropriate discount price for daily perishable products to increase profit from a long-term standpoint. Even if the discount pricing is efficient to increase profit of the day, consumers memorize the sales price and they might hesitate to purchase the product at a regular price the following day. The authors discussed the inventory clearance pricing for a single period in our previous study by constructing a mathematical model to derive an optimal sales price to maximize the expected profit by considering the reference price effect of demand. This paper extends the discussion to handle the discount pricing for multiple periods. A mathematical analysis is first conducted to reveal the properties on an objective function, which is the present value of total expected profits for multiple periods. An algorithm is then proposed to derive an optimal price for asymmetric consumers. Numerical experiments investigate the characteristics of the objective function and optimal pricings.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.30-38
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• 2012

This paper discusses a clearance pricing on daily perishable products considering a reference price of consumers. The daily perishable products are sometimes sold at a discount price before closing time to stimulate demand when the number of unsold products is more than initially envisioned. The discount pricing results both in an increase of the revenue of the day and in a decrease of the disposal cost. The discounting, however, also declines a reference price of consumers which is a mental price and serves as an anchor price to judge if a current sales price is loss or gain for the consumers. An excess discounting decreases the demand for the products sold at a regular price in the future and diminishes long-term profit. This study conducts a mathematical analysis on the clearance pricing problem for a single period with stochastic variations both on demand and on the inventory level at clearance time. The expected profit function especially depends on the response of consumers to the clearing price against their reference prices. A procedure is proposed to derive an optimal clearance price when consumers are loss-neutral. A sufficient condition is shown to obtain an optimal price for loss-averse and loss-seeking consumers by an analogous procedure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.41-54
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• 2019

Although retailers deals with a large number of single-term inventory items, but few cases have been considered in the areas of practical decision making. However, recent moves to strengthen fair trade have created a real need for single-period inventory decision-making problems. This study addresses the problem of ordering quantity decisions that are expected to maximize profits using classical newsvendor models. The research target is data on seasonal and perishable products from retail. We also use data from retailers to actually apply the newsvendor model and calculate the results to compare performance. It also suggests solutions for estimating demand for products sold in order to apply newsvendor models that utilize actual demand ratio versus forecast demand. This study would like to examine the effectiveness of this research through data analysis and make some suggestions for applying it to reality.

• The Journal of Fisheries Business Administration
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• v.30 no.2
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• pp.25-37
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• 1999

Some multi echelon inventory systems carry perishable products. The value of these product reduces as the period of time they spend in the system. In this paper We derive the necessary condition to determine optimal quantity, service level for a perishable product. The systems considered consist of two echelons and carry single item. To determine the optimal order quantity, the demand is assumed to be constant, the holding costs may be different in the echelons, and it allows no shortages. I assumed the price of product decreases by negative exponential function. To determine service level, following assumptions used in the model ㆍlead time is constant. ㆍdemand is normal distribution. ㆍthe product starts to perish at the second echelon. Service level is computed for different levels of lead times and for different variance of demands and for different price functions. The experimental results indicate that the service level in cost is a function of service level in demand and perishability of product. Results of the models exhibit that perishability and the age of the product are critical to determine the lot sizing and service level.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.61-64
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• 2000

This paper analyzes a dynamic lot-sizing problem, in which the order size of multiple products and a single container type are simultaneously considered. In the problem, each order (product) placed in a period is immediately shipped immediately by containers in the period and the total freight cost is proportional to the number of each container type employed. Also, it is assumed that backlogging is not allowed. The objective of this study is to determine the lot-sizes and the shipping policy that minimizes the total costs, which consist of ordering costs, inventory holding costs, and freight costs. Because this problem is NP-hard, we propose a heuristic algorithm with an adjustment mechanism, based on the optimal solution properties. The computational results from a set of simulation experiment are also presented.

• Industrial Engineering and Management Systems
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• v.11 no.3
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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.