Research on Order Quantity Simulation

The order quantity is often affected by various factors, so it is morevaluable to research the problem of evaluating the order quantity based on a less premise. In thispaper, a complicated order quantity problem is studied and an order quantity simulation system isestablished with the simulation software of ARENA. Finally, an example is given.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.

Optimal quality level,order quantity and selling price for the retailer in a two-level supply chain

For a classical order quantity/pricing problem,we present a geometric programming(GP)approach to find the optimal selling price,order quantity and quality level to maximize the profit for the retail firm.Traditional models such as EOQ are not able to handle the nonlinearity of costs and demand.We adopt the GP approach and make a proper transformation of the model so as to solve this classical problem and obtain the global optimal solution.In addition to the optimal solutions,we also perform a sensitivity analysis.The study shows once more that GP is an excellent approach when decision variables interact in a nonlinear,especially exponential manner.

Simultaneous determination of manufacturer’s process mean and production run length,and retailer’s order quantity

In Chen and Liu’s optimum profit model with a traditional production system,they did not consider the effect of product quality on the customer’s demand order quantity,and also ignored the used cost of customers for product.In fact,the customer’s demand quantity is always seriously related to product quality.Hence,in the present paper,we modify Chen and Liu’s model to address the determination of the optimal process parameters by employing the idea of quality loss and single sampling rectifying inspection plan.Assuming that the quality characteristic of the product is normally distributed,Taguchi’s symmetric quadratic quality loss function is applied in evaluating the product quality.Three decision variables,i.e.,the mean of the process characteristic,the production run length of the product and the retailer’s order quantity,are jointly determined in our modified model to maximize the expected total profit of society,which includes both the manufacturer and the retailer.A heuristic solution procedure is developed for this optimization problem,and a numerical example is provided for illustration.From the numerical results,it can be seen that both the sale price per unit and the intercept of the mean demand of the customer are two major(or significant)parameters in the model and should be more accurately estimated in practice.Finally,the quality investment policy is provided to compare its effect on the optimum profit model with quality improvement.

OPTIMAL POLICY WITH A TOTAL ORDER QUANTITY COMMITMENT CONTRACT IN THE PRESENCE OF A SPOT MARKET

In this paper, the optimal policy is considered when the buyer faces two supply sources： one is the contract supplier from which the buyer orders over a specific contract period （say, a year） at a pre-agreed price, and the other is the spot market. However, when ordering from the contract supplier, the buyer must fulfill a pre-determined total order quantity, or the so-called definite total order quantity commitment, over the whole contract period. In other words, the commitment secures the buyer a fixed price but obliges him/her a total order quantity over the contract period. Although the spot market gives the buyer more flexibility in terms of order quantities, its prices are volatile. Such a combination of contract and spot procurements is often observed in practice. Within the contract period, there are multiple sub-periods, during each of which the buyer reviews the inventory, issues an individual order, and uses the on-hand inventory to meet the random demand. Thus, in each （ordering） period, the buyer will weigh between the current known spot price （by procuring from the spot market） and a lower future price （by waiting while consuming the remaining commitment）. An optimal dual ordering policy is characterized for each period, depending on the on-hand inventory level, the spot price, and the remaining commitment quantity. The optimal policy in each period is also shown to be independent of the contract price. Through a numerical study, the inventory cost is demonstrated to be （1） insensitive to the contract price when the total commitment quantity is lower than the total expected demand over the contract period and （2） non-increasing in the variability of spot prices.

Introduction to an Invariant Quantity Method

It is impossible,mathematically, to use a time series which is regarded as a set of observational facts of a dynamicsystem to reconstruct the particular system.Physically, however, with a few assumptions put, a dynamic system canbe rebuilt approximately by means of observational facts.This is the goal of the so called invariant quantity method(IQM),whose research and experiment are of potential significance to atmospheric sciences.

Financial Derivatives Market and Storage Management

It’s known to all that under ideal condition the s to rage cost is kept in lower level when storage management be arranged by Economic Order Quantity(EOQ).Does this mean that any companies should set up their own storing system in proportion to the scale of the commodities’ producing or sell ing Furthermore, even if they manage storage in EOQ, because of different oper ation scale, geographical condition or ability borrowing money from financial ma rket, different companies pay unequal cost in storing the same commodity.In thi s paper, except for supplying commodities from our own storage system, the autho rs have analyzed other two supplying ways without whole storage system, they are forward contracts and futures contracts.The authors have discussed variable su pply cost for above different supply measures.According to the cost of each sup ply way, the managers can choose the most economical way in supplying the commod ity and predict the price of futures from storage management arranged by EOQ.Th e summary content is as follow: 1. The comparing of supply cost between forward contracts and storing system a rranged by EOQ. (1) The supply cost from forward contracts (2) The supply cost from storage system arranged by Economic Order Quantity (3) The application example for comparing cost in different supply way 2.The comparing of supply cost between futures going physical and storing syst em arranged by Economic Order Quantity. (1) The supply cost from futures going physical (2) The correlation between futures contracts and storage management arranged b y EOQ (3) The application example for comparing cost in different supply way 3.How does storing system of scale economic affect the price of forward and fu tures contracts (1) How does the price of forward and futures contracts fluctuate (2) How do we calculate the price of a commodity at future point from the cost of scale economic storing (3) How do we operate efficiently in derivatives market by using the cost of sc ale economic storing (4) The application example for analyzing the price of futures 4.The correlation among storage managementforward contracts and futures mark et.

Modelling Economic Order Quantities,Considering Buy and Repair Options for Defective Items,and Allowing for Shortages and Inspection Errors

Nowadays,it is common for suppliers to be separated from their buyers by great distances.This means that,if some items in the lot turn out to be defective,the distance makes it uneconomical to order replacements from the original supplier.Moreover,both Type I and Type II errors may occur in the screening process for eliminating defective items and the combination of defective items and inspection errors may lead to shortages.Working with these assumptions,this paper develops two distinct models.Under the first model,defective items are repaired by a local repair shop subject to a repair charge and a mark-up margin.Under the second model,a local supplier replaces the defective with good ones,but at a higher cost.The expected total profit per cycle is developed,together with the expected cycle time,and,employing the renewal reward theorem,the objective function is derived,from which the optimum values are obtained for the order and shortage quantities.The paper presents numerical results and a discussion for both models.The study finds that repairing defective items generally leads to greater total profit than purchasing local replacements.

TWO-STAGE ORDERING DECISION FOR A SHORT-LIFE-CYCLE PRODUCT

This paper investigates the ordering decision problem for a short-life-cycle product under Bayesian updating. For a product characterized by a single manufacturing cycle and two selling periods, we depict a Two-Stage （TS） ordering strategy with a stochastic dynamic programming model in the view of the whole system, and prove that the expected profit function of the whole system is concave on the first ordering quantity and the remedial ordering quantity, respectively. Then, the optimal ordering decision is developed. Finally, characteristics of the optimal ordering quantities are analyzed with several examples. Our results show that the suggested TS decision model is better than a Quick Response （QR） decision model.

Multi-objective vendor managed inventory system with interval type-2 fuzzy demand and order quantities

Purpose-The proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer,multi-item and a consolidated vendor store.Regarding demand and order quantities with the deterministic and type-1 fuzzy numbers,we have also formulated the classic/crisp MOVMI model and type-1 fuzzy MOVMI(T1FMOVMI)model.The suggested solution technique can solve both crisp MOVMIand T1FMOVMIproblems.By finding the optimal ordered quantities and backorder levels,the Paretofronts are constructed to form the solution sets for the three models.Design/methodology/approach-A multi-objective vendor managed inventory(MOVMI)is the most recognized marketing and delivery technique for the service provider and the retail in the supply chain in Industry 4.0.Due to the evolving market conditions,the characteristics of the individual product,the delivery period and the manufacturing costs,the demand rate and order quantity of the MOVMI device are highly unpredictable.In such a scenario,a MOVMI system with a deterministic demand rate and order quantity cannot be designed to estimate the highly unforeseen cost of the problem.This paper introduces a novel interval type-2 fuzzy multi-objective vendor managed inventory(IT2FMOVMI)system,which uses interval type-2 fuzzy numbers(IT2FNs)to represent demand rate and order quantities.As the model is an NP-hard,the well-known meta-heuristic algorithm named NSGA-II(Non-dominated sorted genetic algorithm-II)with EKM(Enhanced Karnink-Mendel)algorithm based solution method has been established.Findings-The experimental simulations for the five test problems that demonstrated distinct conditions are considered from the real-datasets of SAPCO company.Experimental study concludes that T1FMOVMI and crisp MOVMI schemes are outclassed by IT2FMOVMI model,offering more accurate Pareto-Fronts and efficiency measurement values.Originality/value-Using fuzzy sets theory,a significant amount of work has been already done in past decades from various points of views to model the MOVMI.However,this is the very first attempt to introduce type-2 fuzzy modelling for the problem to address the realistic implementation of the imprecise parameters.

A RISK-AVERSE NEWSVENDOR MODEL WITH LIMITED CAPACITY AND OUTSOURCING UNDER THE CVAR CRITERION

For seasonal products, the retailers usually launch various marketing ettorts, llKe aaverusmg tmu promotion, to promote them in a selling season. While facing large demand from the customers, one should take the capacity constraint and outsotlrcing into consideration. Considering the shorten life cycles of most products, in this paper we adopt the traditional newsvendor model to investigate the optimal marketing effort along with optimal order quantity. We address the risk aversion issue and characterize the influence of the sellers＇ risk propensity with CVaR criterion, and we develop an effective algorithm to obtain the optimal strategy. The impact of sellers＇ risk propensity on the performance of the system is illustrated via numerical examples, The innovation of this paper is threefold. First, the optimal joint strategy of the marketing effort and order quantity is investigated and an efficient algorithm to find the optimal strategy is developed. Second, the capacity constraint option and an outsourcing strategy are studied jointly for excess products. Finally, the risk propensity of the seller and its influence are investigated by using the CVaR criterion, through which we obtain some new managerial insights.

Centralized Decisions for a Two-Stage Supply Chain with Price-Discount Dependent Demand

In this paper,we study a centralized supply chain for a two-stage with selling price discount.This supply chain consists of a supplier and a retailer. Based on the feature that the product’s selling season is short and the supply chain faces great demand uncertainty. We consider a two-stage scenario where,at the beginning of stage 1,the supplier reserves production capacity based on historic data in advance,stage 2 comes to us after some leadtime,both the supplier and the retailer update the demand information,the retailer then places an order not exceeding the reserved capacity based on the selling-pricing discount dependent demand. We make optimal decisions on the reserved capacity in stage 1,selling price discount and order quantity in stage 2. In this supply chain,the pattern in stage2 is figured out first,and then stage 1 is cleared as well. Then we present a numerical example to give some insights. Finally we get some conclusions.

EMISSION ABATEMENT FOR PRODUCTION SYSTEM ACROSS LOCATIONS WITH HETEROGENEOUS EMISSION PROFLES

This paper investigates a production system in which the desired system state is a reduction of emissions and the controlling action plan is altering carbon price. From the operations perspective, we develop a model to study how increasing carbon emission costs may affect the joint production and location decisions for a manufacturer across different locations. Specifically, our model incorporates economies of scale and explicitly links product demand, production costs and carbon emission levels to location decisions. The firm＇s decisions in production batch size and locations are then optimised. The system state of emission are analysed under different carbon prices. Finally we check the alignment of objectives in costs and emissions for the system. The results show that for a production system with economies of scale, the production allocation is transformed to a location choice problem after optimising the costs. Raising the carbon price reduces the carbon emissions but may not be able to induce the production to be placed in an emission efficient place. We propose a hybrid policy combining carbon price and free emission allowance to fully align the cost efficiency and emission efficiency and characterise the link between the emission target and the carbon price.

Optimal inventory policies for short life cycle successive generations’ technology products

In this paper,a new Economic Order Quantity(EOQ)model for a successive generation of technology products has been discussed.The classical EOQ model is based on the assumption that the demand rate is constant.Hence it cannot be used for technology products where competition-substitution among products is a usual phenomenon.To address this problem,the EOQ model proposed in this article is considered a demand model for a technology product that follows the innovation-diffusion process.A numerical example has been illustrated and a comprehensive sensitivity analysis is conducted to understand the path of the optimal planning horizon and optimal costs under varied innovation and imitation effect.The sensitivity analysis of the introduction timing of the second generation has been performed to know the applicability of the model in actual circumstances.The behavior of the model has been discussed in detail in the numerical illustration section.