On a queueing-inventory with reservation, cancellation, common life time and retrial

Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Krishnamoorthy, A. [verfasserIn] Shajin, Dhanya [verfasserIn] Lakshmy, B. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Reservation Cancellation Common life time Queueing-inventory system Retrial queue

Übergeordnetes Werk:	Enthalten in: Annals of operations research - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984, 247(2015), 1 vom: 04. Apr., Seite 365-389
Übergeordnetes Werk:	volume:247 ; year:2015 ; number:1 ; day:04 ; month:04 ; pages:365-389

Links:	Volltext

DOI / URN:	10.1007/s10479-015-1849-x

Katalog-ID:	SPR010648801

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520			\|a Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed.
650		4	\|a Reservation \|7 (dpeaa)DE-He213
650		4	\|a Cancellation \|7 (dpeaa)DE-He213
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650		4	\|a Retrial queue \|7 (dpeaa)DE-He213
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700	1		\|a Lakshmy, B. \|e verfasserin \|4 aut
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author_variant	a k ak d s ds b l bl
matchkey_str	article:15729338:2015----::nqeenivnoyiheevtocneltocm
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allfields	10.1007/s10479-015-1849-x doi (DE-627)SPR010648801 (SPR)s10479-015-1849-x-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 85.03 bkl Krishnamoorthy, A. verfasserin aut On a queueing-inventory with reservation, cancellation, common life time and retrial 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed. Reservation (dpeaa)DE-He213 Cancellation (dpeaa)DE-He213 Common life time (dpeaa)DE-He213 Queueing-inventory system (dpeaa)DE-He213 Retrial queue (dpeaa)DE-He213 Shajin, Dhanya verfasserin aut Lakshmy, B. verfasserin aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 247(2015), 1 vom: 04. Apr., Seite 365-389 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:247 year:2015 number:1 day:04 month:04 pages:365-389 https://dx.doi.org/10.1007/s10479-015-1849-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.03 ASE AR 247 2015 1 04 04 365-389
spelling	10.1007/s10479-015-1849-x doi (DE-627)SPR010648801 (SPR)s10479-015-1849-x-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 85.03 bkl Krishnamoorthy, A. verfasserin aut On a queueing-inventory with reservation, cancellation, common life time and retrial 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed. Reservation (dpeaa)DE-He213 Cancellation (dpeaa)DE-He213 Common life time (dpeaa)DE-He213 Queueing-inventory system (dpeaa)DE-He213 Retrial queue (dpeaa)DE-He213 Shajin, Dhanya verfasserin aut Lakshmy, B. verfasserin aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 247(2015), 1 vom: 04. Apr., Seite 365-389 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:247 year:2015 number:1 day:04 month:04 pages:365-389 https://dx.doi.org/10.1007/s10479-015-1849-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.03 ASE AR 247 2015 1 04 04 365-389
allfields_unstemmed	10.1007/s10479-015-1849-x doi (DE-627)SPR010648801 (SPR)s10479-015-1849-x-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 85.03 bkl Krishnamoorthy, A. verfasserin aut On a queueing-inventory with reservation, cancellation, common life time and retrial 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed. Reservation (dpeaa)DE-He213 Cancellation (dpeaa)DE-He213 Common life time (dpeaa)DE-He213 Queueing-inventory system (dpeaa)DE-He213 Retrial queue (dpeaa)DE-He213 Shajin, Dhanya verfasserin aut Lakshmy, B. verfasserin aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 247(2015), 1 vom: 04. Apr., Seite 365-389 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:247 year:2015 number:1 day:04 month:04 pages:365-389 https://dx.doi.org/10.1007/s10479-015-1849-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.03 ASE AR 247 2015 1 04 04 365-389
allfieldsGer	10.1007/s10479-015-1849-x doi (DE-627)SPR010648801 (SPR)s10479-015-1849-x-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 85.03 bkl Krishnamoorthy, A. verfasserin aut On a queueing-inventory with reservation, cancellation, common life time and retrial 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed. Reservation (dpeaa)DE-He213 Cancellation (dpeaa)DE-He213 Common life time (dpeaa)DE-He213 Queueing-inventory system (dpeaa)DE-He213 Retrial queue (dpeaa)DE-He213 Shajin, Dhanya verfasserin aut Lakshmy, B. verfasserin aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 247(2015), 1 vom: 04. Apr., Seite 365-389 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:247 year:2015 number:1 day:04 month:04 pages:365-389 https://dx.doi.org/10.1007/s10479-015-1849-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.03 ASE AR 247 2015 1 04 04 365-389
allfieldsSound	10.1007/s10479-015-1849-x doi (DE-627)SPR010648801 (SPR)s10479-015-1849-x-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 85.03 bkl Krishnamoorthy, A. verfasserin aut On a queueing-inventory with reservation, cancellation, common life time and retrial 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed. Reservation (dpeaa)DE-He213 Cancellation (dpeaa)DE-He213 Common life time (dpeaa)DE-He213 Queueing-inventory system (dpeaa)DE-He213 Retrial queue (dpeaa)DE-He213 Shajin, Dhanya verfasserin aut Lakshmy, B. verfasserin aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 247(2015), 1 vom: 04. Apr., Seite 365-389 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:247 year:2015 number:1 day:04 month:04 pages:365-389 https://dx.doi.org/10.1007/s10479-015-1849-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.03 ASE AR 247 2015 1 04 04 365-389
language	English
source	Enthalten in Annals of operations research 247(2015), 1 vom: 04. Apr., Seite 365-389 volume:247 year:2015 number:1 day:04 month:04 pages:365-389
sourceStr	Enthalten in Annals of operations research 247(2015), 1 vom: 04. Apr., Seite 365-389 volume:247 year:2015 number:1 day:04 month:04 pages:365-389
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Reservation Cancellation Common life time Queueing-inventory system Retrial queue
dewey-raw	004
isfreeaccess_bool	false
container_title	Annals of operations research
authorswithroles_txt_mv	Krishnamoorthy, A. @@aut@@ Shajin, Dhanya @@aut@@ Lakshmy, B. @@aut@@
publishDateDaySort_date	2015-04-04T00:00:00Z
hierarchy_top_id	320615421
dewey-sort	14
id	SPR010648801
language_de	englisch
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author	Krishnamoorthy, A.
spellingShingle	Krishnamoorthy, A. ddc 004 bkl 85.03 misc Reservation misc Cancellation misc Common life time misc Queueing-inventory system misc Retrial queue On a queueing-inventory with reservation, cancellation, common life time and retrial
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topic_title	004 ASE 85.03 bkl On a queueing-inventory with reservation, cancellation, common life time and retrial Reservation (dpeaa)DE-He213 Cancellation (dpeaa)DE-He213 Common life time (dpeaa)DE-He213 Queueing-inventory system (dpeaa)DE-He213 Retrial queue (dpeaa)DE-He213
topic	ddc 004 bkl 85.03 misc Reservation misc Cancellation misc Common life time misc Queueing-inventory system misc Retrial queue
topic_unstemmed	ddc 004 bkl 85.03 misc Reservation misc Cancellation misc Common life time misc Queueing-inventory system misc Retrial queue
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title	On a queueing-inventory with reservation, cancellation, common life time and retrial
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title_full	On a queueing-inventory with reservation, cancellation, common life time and retrial
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title_sort	on a queueing-inventory with reservation, cancellation, common life time and retrial
title_auth	On a queueing-inventory with reservation, cancellation, common life time and retrial
abstract	Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed.
abstractGer	Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed.
abstract_unstemmed	Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed.
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title_short	On a queueing-inventory with reservation, cancellation, common life time and retrial
url	https://dx.doi.org/10.1007/s10479-015-1849-x
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author2	Shajin, Dhanya Lakshmy, B.
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doi_str	10.1007/s10479-015-1849-x
up_date	2024-07-03T17:27:06.500Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR010648801</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110221237.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2015 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10479-015-1849-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR010648801</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10479-015-1849-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">85.03</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Krishnamoorthy, A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">On a queueing-inventory with reservation, cancellation, common life time and retrial</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In this paper we model a queueing-inventory system that has applications in railway and airline reservation systems. Maximum items in the inventory is %$S%$ which have a random common life time; this includes those that are sold in particular cycle. A customer, on arrival to an idle server with at least one item in inventory, is immediately taken for service; or else he joins the buffer of maximum size %$S%$ depending on number of items in the inventory (the buffer capacity varies and is, at any time, equal to the number of items in the inventory). The arrival of customers constitutes a Poisson process, demanding exactly one item each from the inventory. If there is no item in the inventory, the arriving customer first queue up in a finite waiting space of capacity %$K%$. When it overflows an arrival goes to an orbit of infinite capacity with probability %$p%$ or is lost forever with probability %$1-p%$. From the orbit he retries for service according to an exponentially distributed inter-occurrence time. The service time follows an exponential distribution. Cancellation of sold items before its expiry is permitted. Inventory gets added through cancellation of purchased items, until the expiry time. Cancellation time is assumed to be negligible. We analyze this system. Several performance characteristics are computed; expected sojourn time of the system in a cycle with “no inventory” and also “maximum inventory” are computed. Some illustrative numerical examples are presented. An optimization problem is numerically analyzed.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Reservation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cancellation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Common life time</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Queueing-inventory system</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Retrial queue</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shajin, Dhanya</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lakshmy, B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Annals of operations research</subfield><subfield code="d">Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984</subfield><subfield code="g">247(2015), 1 vom: 04. 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