Modular design of multi-species multi-level

inventory optimization system simulation

Tiening Wang Academy of Armored Forces

Engineering Beijing, China

Rongbo Ke Academy of Armored Forces

Engineering Beijing, China

daxiaoke1985@126.com

Shengliang Xu Academy of Armored Forces

Engineering

Beijing, China

Abstract-In this paper, we study and design the

multi-species multi-level inventory optimization system

Simulation. In the system, we set up the multi-level inventory

model firstly, and then run the simulation. Regarding cost and

supply ability as the goal, the system optimizes the inventory

control and inventory structure. Using the concept of modular

design, technology of interface-oriented and many good design

patterns, system is divided into smaller modules, which is

independent and complete. So we realize the decoupling of

these modules. The scalability, reusability and maintainability

have been greatly improved.

Keywords-Inventory; Modular design; interface-oriented

I. INTRODUCTION

Inventory refers to the goods or commodities that are in storage state. No matter to enterprise or army, there are its important meanings in scientific inventory control. Enterprises regard reducing the cost, increasing economic efficiency as the basic goal, while the army pays more attention to the military benefit. How to make the scientific inventory control strategy so as to ensure the army fights and trains the need, is the primary goal of military, to reduce the cost is a second goal. Different goals of inventory management lead to different optimize strategy and varied consumption law, so the general inventory simulation system is unable to meet the varied demand of setting up models or running the simulation. In this paper, by using the concept of modular design, technology of interface-oriented and several good design patterns, the

simulation system is well realized. Furthermore, it has been greatly improved in scalability, portability and maintainability.

II. MULTI-LEVEL INVENTORY SYSTEM MODEL

A. General description of model

Figure 1. Generial description of model

Inventory system mainly consists of entities, relationships, and control strategy.

B. Entity

By analyzing the supply chain processes, the system is divided into factory, warehouse and consumption department. As the source of goods produced, factory is the top level of the logistics supply chain entity, while consumption department is the lowest level entities:

Factory entity. According to the order task, factory products goods and then supply to lower. Goods warehouse entity. Warehouse storage goods and order to upper warehouse or factory according to its order policy. Consumption department entity. Consumption department create random consumption according to consumption law, and ask for goods from upper.

2011 International Conference on Instrumentation, Measurement, Computer, Communication and Control

978-0-7695-4519-6/11 $26.00 © 2011 IEEE

DOI 10.1109/IMCCC.2011.112

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C. Relation

In design of the multi-level inventory system model, entities are related by application and supplement:

Application relationship means the lower apply to the upper layer entity for goods. It can be seen as an information flow, each application contains the order type, quantity, time and other information. Supply relationship means the higher supply goods to the lower. It can be seen as a real good flow..

D. Control strategy

This system is mainly controlled from five aspects: the production, ordering, consumption, cost and support capabilities.

1) Production control. Factory production control major decisions required to complete a number of production tasks time T:

: Fixed production preparation time n: The number of goods types in this order task

: The first i-order quantity -- The first i-production rate

2) Order control strategy. Orde policys are of many types, we use the following four common strategies:

a) (Q, s) strategy. Check inventory continuously, when the inventory reduces to the reorder point s , make an order whose quantity is a fixed value of Q. The policy fits to high demand, high cost or volatile demand situation.

b) (Q, s) strategy. To check the inventory status at any time, when the inventory reduces to the reorder point s, make an order that can lift havingsum to the constant S. The difference from (Q,s) is that its order quantity is determined by physical inventory, so order quantity is variable.

c) (t, S) policy. Check every certain period of time, and issued an order to supplement existing stocks to the maximum inventory level S. This policy applies to some good that is not very important, or very useful.

d) (t, s, S) policy. The strategy is the strategy (t, S) and strategy (R, s) synthesis. When the check after a certain period t and if the stock below the order point, make an order.

3) Consumption control. In this system, consumption department produces a consume every time T.

4) Calculation of the cost. In this system, we mainly considered four types of cost which are order preparation cost, goods cost, transportation cost and maintenance cost.

Cost of order preparation:

: A fixed unit cost of order k:The total batch number of orders

: The number of goods types in the first i-order Cost of goods:

: The first j-order quantity in the first i-order : The unit price of the frist j-goods

: The first j-goods discount in the first i-order Cost of transportation:

: Transport Unit price of the first i-goods : Correction factor of the first i-batch. Cost of maintenance

:The unit maintenance price of the frist j-goods :Number of frist j-goods in frist i- maintenance

5) Support capability. To the army, support rate is a key indicator to measure inventory management rationality.

: The importance of the frist i-goods : Simulation start time : Simulation end time

:The owed number of the frist i-goods at time t

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III. MODULAR DESIGN OF SYSTEM

A. Overall design of system functions

The system mainly accomplished consumption analysis, model base management, simulation and modeling, optimization and other functions.

Figure 2. System structure

B. Overall design of system architecture

Event scheduling is modeling flexibility and wide application, which fits for the system that components associated small, but the event handling routines and modeling workload. So we use event scheduling simulation algorithm as the basis of the system. System is developed in the dot net environment of Microsoft, coding by C# language, and running at dot net framework2.0 or higher.

By the modular design, the system is divided into 10 modules, which are control strategy, simulation event, optimization, entities model library etc.

Figure 3. Software overall structure

C. Design of main module and algorithm

Control module consists mainly of order policy, cost calculation and consumption control strategies.

Figure 4. Class view and inheritance of order

The system control strategy of all has a common base class Policy_Super. Order policy which was designed with a simple factory pattern, 4 common order control strategies are implemented by four class which are all co-inherited from the abstract class OrderPolicy, ordering strategies class provides the only interface IorderPolicy. External program can instantiates order policy by calling the factory class OrderPolicyFactory Factory static function.

IV. SYSTEM RUNNING

A. Case description

In this paper, we pick Military L for study. Military L has vast jurisdiction, since information sharing is low and transport is not convenient and other factors, it leads to the supply of some equipment cannot meet demand. And some department in order to ensure the equipment support capabilities simply increases equipment inventories, resulting in some more serious equipment inventory, equipment and maintenance costs are higher.

B. System running

According to L military structure to model multi-level inventory, select two typical devices of X, Y, set the corresponding control strategy and simulation environment, simulation time to 30 years, the optimal period of 3 years for simulation, then run the simulation.

C. Optimization analysis

Military L warehouse’s two equipments optimization process is shown below: the broken line in the upper half of two picture express adjustment course, while the curve and block diagram in the other half show support rate and cost

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respectively.The upper figure show the optimization process of

equipment X. After 9 cycles of optimization, the cost of equipment X decreased 79.76%, while the support rate is still maintained at 100%. The lower one show the Y’s. It’s support rate has been left up to rate 100%, meaning increased 55.01% than the original. What is opposite to support rate, that we reduced the cost of 12.67%.

Figure 5. Optimization process of X,Y

The results of simulation and optimization of each department are shown as figure8: After optimization, Military L warehouses, Military L repair brigade and warehouse L1s’ support rate increased by 21.57%, 18.18% and 0%, to 100%, 96.99% and 100%. After optimized inventory control strategy, the costs decrease by 70% or so.

Figure 6. Optimization result

V. CONCLUSION

In this paper, by using the modular design concept and the interface-oriented techniques, the simulation system is divided into separate modules for each function, by which it achieves a decoupling between the module, and ensures the structure and function of each module independence And completeness. All of the various functional modules constitute a comprehensive integration of the entire system to meet the diverse needs of the general inventory model, while greatly improving the system scalability, reusability and maintainability.

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