Two storage inventory model of a deteriorating item with variable demand under partial credit period

被引:45
作者
Guchhait, Partha [1 ]
Maiti, Manas Kumar [2 ]
Maiti, Manoranjan [1 ]
机构
[1] Vidyasagar Univ, Dept Appl Math, Paschim Medinipur 721102, W Bengal, India
[2] Mahishadal Raj Coll, Dept Math, Purba Medinipur 721628, W Bengal, India
关键词
Particle Swarm-Genetic Algorithm; Variable demand; Deterioration; Permissible delay in payment; ECONOMIC ORDER QUANTITY; STOCK-DEPENDENT DEMAND; FUZZY LEAD-TIME; GENETIC ALGORITHM; PERMISSIBLE DELAY; POSSIBILITY CONSTRAINTS; PAYMENTS; 2-WAREHOUSE; WAREHOUSES; BACKORDER;
D O I
10.1016/j.asoc.2012.07.028
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a two-warehouse inventory model for deteriorating item with stock and selling price dependent demand has been developed. Above a certain (fixed) ordered label, supplier provides full permissible delay in payment per order to attract more customers. But an interest is charged by the supplier if payment is made after the said delay period. The supplier also offers a partial permissible delay in payment even if the order quantity is less than the fixed ordered label. For display of goods, retailer has one warehouse of finite capacity at the heart of the market place and another warehouse of infinite capacity (that means capacity of second warehouse is sufficiently large) situated outside the market but near to first warehouse. Units are continuously transferred from second warehouse to first and sold from first warehouse. Combining the features of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) a hybrid heuristic (named Particle Swarm-Genetic Algorithm (PSGA)) is developed and used to find solution of the proposed model. To test the efficiency of the proposed algorithm, models are also solved using another two established heuristic techniques and results are compared with those obtained using proposed PSGA. Here order quantity, refilling point at first warehouse and mark-up of selling price of fresh units are decision variables. Models are formulated for both crisp and fuzzy inventory parameters and illustrated with numerical examples. (C) 2012 Elsevier B. V. All rights reserved.
引用
收藏
页码:428 / 448
页数:21
相关论文
共 35 条
[1]   Weighted trapezoidal approximation-preserving cores of a fuzzy number [J].
Abbasbandy, S. ;
Hajjari, T. .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2010, 59 (09) :3066-3077
[2]   ORDERING POLICIES OF DETERIORATING ITEMS UNDER PERMISSIBLE DELAY IN PAYMENTS [J].
AGGARWAL, SP ;
JAGGI, CK .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 1995, 46 (05) :658-662
[3]   The development of a changing range genetic algorithm [J].
Amirjanov, A .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2006, 195 (19-22) :2495-2508
[4]   Inventory model with fuzzy lead-time and dynamic demand over finite time horizon using a multi-objective genetic algorithm [J].
Bera, U. K. ;
Maiti, M. K. ;
Maiti, M. .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2012, 64 (06) :1822-1838
[5]   A genetic algorithm with real-value coding to optimize multimodal continuous functions [J].
Bessaou, M ;
Siarry, P .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2001, 23 (01) :63-74
[6]  
Bhunia AK, 1998, J OPER RES SOC, V49, P287, DOI 10.1057/palgrave.jors.2600512
[7]   Economic reorder point for fuzzy backorder quantity [J].
Chang, SC ;
Yao, JS ;
Lee, HM .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1998, 109 (01) :183-202
[8]   Lot-sizing decisions under trade credit depending on the ordering quantity [J].
Chung, KJ ;
Liao, JJ .
COMPUTERS & OPERATIONS RESEARCH, 2004, 31 (06) :909-928
[9]  
Engelbrecht AP., 2005, Fundamentals of computational swarm intelligence
[10]   An inventory model for deteriorating items with stock-dependent demand rate [J].
Giri, BC ;
Pal, S ;
Goswami, A ;
Chaudhuri, KS .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1996, 95 (03) :604-610