@article{Pukcarnon201453,

title = {The can-order policy for one-warehouse r-retailer inventory system: A heuristic approach},

author = {Varaporn Pukcarnon and Paveena Chaovalitwongse and Naragain Phumchusri},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908504006&doi=10.4186%2fej.2014.18.4.53&partnerID=40&md5=a4e0b78a2c02a1cc88866df1a0714293},

doi = {10.4186/ej.2014.18.4.53},

year  = {2014},

date = {2014-01-01},

journal = {Engineering Journal},

volume = {18},

number = {4},

pages = {53 – 72},

publisher = {Chulalongkorn University 1},

abstract = {We study an application of the can-order policy in one-warehouse n-retailer inventory systems, and propose a heuristic approach for setting the appropriate inventory policy. On the can-order policy, an order is triggered when a retailer’s inventory position reaches its must-order level. Then other retailers are examined whether their inventory reaches their can-order level, and if so they are filled by this order as well. Warehouse fulfills all involved retailers’ inventory to their order-up-to levels. The can-order policy is not only able to save the total system-wide cost from joint replenishment, but it is also simple to use. Computer simulation is utilized to preliminarily study and to determine the best-known solution. We propose a heuristic approach utilizing the decomposition technique, iterative procedure, and golden section search to obtain the satisfying total system-wide cost. This can save our computational time to find the appropriate inventory policy setting from the reduced search space. We found that the proposed heuristic approach performs very well with the average cost gap of less than 2% comparing to the best-known solution. Thus, the can-order policy can be very useful for such systems. © 2014 Chulalongkorn University 1. All rights reserved.},

note = {Cited by: 5; All Open Access, Bronze Open Access, Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Phumchusri201456,

title = {Scaling the house: Optimal seating zones for entertainment venues when location of seats affects demand},

author = {Naragain Phumchusri and Julie L. Swann},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922562247&doi=10.1504%2fIJRM.2014.067334&partnerID=40&md5=636ca4823e863909fbf1e0954f6fe8d2},

doi = {10.1504/IJRM.2014.067334},

year  = {2014},

date = {2014-01-01},

journal = {International Journal of Revenue Management},

volume = {8},

number = {1},

pages = {56 – 98},

publisher = {Inderscience Publishers},

abstract = {This paper studies the problem of 'Scaling the House', or how venue managers should optimally divide seats into sections with different prices. From previous study, it was found that distance from the stage and distance from the seating row's centre affect demand. We develop a two-dimensional zoning model for the optimal 'Scaling the House' decisions. When demand is not significantly sensitive to distance from the centre, we present an alternative one-dimensional zoning model and show that the optimal seating row (to be priced at a higher price before switching to the next lower price) is the row whose expected revenue when charging at a high price is equal to the expected revenue when charging at a low price. We provide key comparative statics on how model parameters impact the optimal decisions and discuss the important managerial insights on when it is most worthwhile to section seats into two dimensional zones. Copyright © 2014 Inderscience Enterprises Ltd.},

note = {Cited by: 6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}