Optimal sales policy for a class of non-perishable items from fixed capacity over finite horizons

Author(s):  
Xiao-qin Wen ◽  
Qi-ying Hu
2018 ◽  
Vol 15 (3) ◽  
pp. 306-346 ◽  
Author(s):  
Vaibhav Chaudhary ◽  
Rakhee Kulshrestha ◽  
Srikanta Routroy

PurposeThe purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps.Design/methodology/approachIn total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested.FindingsThere are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market.Research limitations/implicationsOnly peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling.Practical implicationsStress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory.Originality/valueThe current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.


2012 ◽  
Author(s):  
Christian-Oliver Ewald ◽  
Aihua Zhang ◽  
Charles Nolan

2001 ◽  
Vol 356 (1413) ◽  
pp. 1483-1491 ◽  
Author(s):  
N. S. Clayton ◽  
D. P. Griffiths ◽  
N. J. Emery ◽  
A. Dickinson

A number of psychologists have suggested that episodic memory is a uniquely human phenomenon and, until recently, there was little evidence that animals could recall a unique past experience and respond appropriately. Experiments on food–caching memory in scrub jays question this assumption. On the basis of a single caching episode, scrub jays can remember when and where they cached a variety of foods that differ in the rate at which they degrade, in a way that is inexplicable by relative familiarity. They can update their memory of the contents of a cache depending on whether or not they have emptied the cache site, and can also remember where another bird has hidden caches, suggesting that they encode rich representations of the caching event. They make temporal generalizations about when perishable items should degrade and also remember the relative time since caching when the same food is cached in distinct sites at different times. These results show that jays form integrated memories for the location, content and time of caching. This memory capability fulfils Tulving's behavioural criteria for episodic memory and is thus termed ‘episodic–like’. We suggest that several features of episodic memory may not be unique to humans.


1988 ◽  
Vol 26 (1) ◽  
pp. 57-61 ◽  
Author(s):  
Frederick Van Der Ploeg ◽  
Giancarlo Marini
Keyword(s):  

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