A particle swarm optimization for solving joint pricing and lot-sizing problem with fluctuating demand and unit purchasing cost

被引：27

作者：

Dye, Chung-Yuan ^{[2
]}

Hsieh, Tsu-Pang ^{[1
]}

机构：

[1] Aletheia Univ, Dept Business Management, Taipei 251, Taiwan

[2] Shu Te Univ, Dept Business Management, Kaohsiung 824, Taiwan

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2010年 / 60卷 / 07期

关键词：

Pricing; Inventory; Partial backlogging; Particle swarm optimization; Fluctuating cost; Inflation; OPTIMAL REPLENISHMENT POLICIES; DETERIORATING ITEM;

D O I：

10.1016/j.camwa.2010.07.023

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we extend the classical economic order quantity model to allow for not only a function of price-dependent and time-varying demand but also fluctuating unit purchasing cost. The joint replenishment problem is subject to continuous decay and a general partial backlogging rate. The objective is to find the optimal replenishment number, time scheduling and periodic selling price to maximize the discounted total profit. An effective search procedure is provided to find the optimal solution by employing the properties derived in this paper and particle swarm optimization algorithm. Several numerical examples are used to illustrate the features of the proposed model. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.

引用

页码：1895 / 1907

页数：13

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