A particle swarm optimization for solving joint pricing and lot-sizing problem with fluctuating demand and trade credit financing

被引:43
作者
Dye, Chung-Yuan [1 ]
Ouyang, Liang-Yuh [2 ]
机构
[1] Shu Te Univ, Dept Business Management, Kaohsiung 824, Taiwan
[2] Tamkang Univ, Grad Inst Management Sci, Taipei 251, Taiwan
关键词
Inventory; Time-varying demand; Deteriorating items; Trade credit financing; Particle swarm optimization; ECONOMIC ORDER QUANTITY; POLICY INVENTORY MODEL; PERMISSIBLE DELAY; EOQ MODEL; DETERIORATING ITEM; LINEAR TREND; SUPPLY CHAIN; TIME; SHORTAGES; PAYMENTS;
D O I
10.1016/j.cie.2010.10.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Pricing is a major strategy for a retailer to obtain its maximum profit. Furthermore, under most market behaviors, one can easily find that a vendor provides a credit period (for example 30 days) for buyers to stimulate the demand, boost market share or decrease inventories of certain items. Therefore, in this paper, we establish a deterministic economic order quantity model for a retailer to determine its optimal selling price, replenishment number and replenishment schedule with fluctuating demand under two levels of trade credit policy. A particle swarm optimization is coded and used to solve the mixed-integer nonlinear programming problem by employing the properties derived in this paper. Some numerical examples are used to illustrate the features of the proposed model. (c) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:127 / 137
页数:11
相关论文
共 33 条