WW(SCperf)
WW()所属R语言包:SCperf
The Wagner-Whitin algorithm
这是The Wagner-Whitin算法
译者:生物统计家园网 机器人LoveR
描述----------Description----------
WW implements the Wagner-Whitin algorithm. Considering time-varying demand, the algorithm builds production plans that minimizes the total setup and holding costs in a finite horizon of time, assuming zero starting inventory and no backlogging.
WW实现的Wagner-Whitin算法。考虑到随时间变化的需求,该算法生成生产计划,最大限度地减少了设置和持有成本,在有限的时间地平线,假设零开始的库存并没有短缺量拖后。
用法----------Usage----------
WW(x,a,h,method=c("forward","backward"))
## Default S3 method:[默认方法]
WW(x,a,h,method=c("forward","backward"))
## S3 method for class 'WW'
print(x, ...)
参数----------Arguments----------
参数:x
a numeric vector containing the demand per unit time,
一个数值向量,包含每单位时间的需求,
参数:a
a numeric vector containing the set-up cost per unit time,
一个数值向量含有的每单位时间的设置成本,
参数:h
a numeric vector containing the holding cost per unit time,
含有的每单位时间的成本保持一个数值向量,
参数:method
character string specifing which algorithm to use, must be "forward" (default) or "backward".
要使用的算法的字符的字符串specifing的,必须是“前进”(默认)或“落后”。
参数:...
not used.
不被使用。
值----------Value----------
WW.default (the function that is called when using WW) returns a list containing:
WW.default(函数被调用时使用WW)返回一个列表,其中包含:
参数:TVC
total variable cost,
总可变成本,
参数:Jt
last period of production for the forward algorithm or the (end of the) period when the inventory reaches a zero level for the backward algorithm,
去年同期生产前向算法(结束)期间,当库存达到零水平落后算法,
参数:Solution
matrix of solutions.
矩阵的解决方案。
(作者)----------Author(s)----------
Marlene Silva Marchena <a href="mailto:marchenamarlene@gmail.com">marchenamarlene@gmail.com</a>
参考文献----------References----------
Sweden: Springer, Second Edition.
operational research. New York: McGraw-Hill, Seventh Edition.
参见----------See Also----------
EOQ, EPQ, Newsboy
EOQ,EPQ,Newsboy
实例----------Examples----------
# Example from Hiller, p.952, reproduced bellow: [例如从希勒,p.952,转载波纹管:]
# An airplane manufacturer specializes in producing small airplanes. It has just received an[飞机制造商专门生产小型飞机。刚收到的]
# order from a major corporation for 10 customized executive jet airplanes for the use[为了从一个大公司,10个定制的喷气公务机飞机的使用]
# of the corporation's upper management. The order calls for three of the airplanes to be[该公司的高层管理人员。该命令的调用三的飞机]
# delivered (and paid for) during the upcoming winter months (period 1), two more to be delivered[在即将到来的冬季(第1期),交付交付(支付)]
# during the spring (period 2), three more during the summer (period 3),and[弹簧(周期2),三个以上的夏季期间(周期3)中,和期间]
# the final two during the fall (period 4). Setting up the production facilities to meet[在秋季的最后两个(4期)。设置生产设施,以满足]
# the corporation's specifications for these airplanes requires a setup cost of $2 million.[该公司的规格为这些飞机需要200万美元的安装成本。]
# The manufacturer has the capacity to produce all 10 airplanes within a[制造商有能力生产10架飞机在]
# couple of months, when the winter season will be under way. However, this would necessitate holding[几个月内,在冬季时将正在进行。然而,这将需要保持]
# seven of the airplanes in inventory, at a cost of $200,000 per airplane per period, until their[7库存的飞机,每架飞机每周期20万美元的成本,直到他们]
# scheduled delivery times (...)[预定的交货时间(...)]
# Management would like to determine theleast costly production schedule for filling this order.[管理层想填补这个顺序来确定,知道不重要的东西是什么昂贵的生产进度。]
x <- c(3,2,3,2)
a <- c(2,2,2,2)
h <- c(0.2,0.2,0.2,0.2)
WW(x,a,h,method="forward") # forward algorithm[向前算法]
WW(x,a,h,method="backward") # backward algorithm[后向算法]
# The optimal production schedules for the forward and backward case is to:[的向前和向后的情况下的最优生产时间表是:]
# 1. Produce in period 1 for periods 1, 2, 3 and 4 (3 + 2 + 3 + 2 = 10 airplanes)[1。在时期1期1,2,3,4(3 + 2 + 3 + 2 = 10架飞机的生产)]
# Total variable cost $4.8 million.[总可变成本480万美元。]
# 2. Produce in period 1 for periods 1 and 2 (3 + 2 = 5 airplanes) and in period 3[2。生产周期1和2(3 + 2 = 5架飞机)在时期1和第3期]
# for periods 3 and 4 (3 + 2 = 5 airplanes)[期间3和第4(3 + 2 = 5架飞机)]
# Total variable cost $4.8 million.[总可变成本480万美元。]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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