Optimization of the Operating Parameters of Transport and Warehouse Complexes

Optimization of the Operating Parameters of Transport and Warehouse Complexes

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Transportation Research Procedia 00 (2018) 000–000

Transportation Research Procedia 30 (2018) 236–244 www.elsevier.com/locate/procedia

EURO Mini Conference on "Advances in Freight Transportation and Logistics" (emc-ftl-2018) EURO Mini Conference of on "Advances in FreightParameters Transportation of andTransport Logistics" (emc-ftl-2018) Optimization the Operating and

Warehouse Optimization of the OperatingComplexes Parameters of Transport and a Warehouse Vladimir Shepeleva*, Zlata Almetova , OlegComplexes Larinb, Sergey Shepelevc, Olga Issenovaa a South Ural State University,a76 Lenin Avenue, Chelyabinsk c 454080, Russia Vladimir Shepelev *, Zlata Almetova , Oleg Larinb, Sergey Shepelev , Olga Issenovaa Russian Institute for Strategic Studies, 15-B Flotskaya str., Moscow 125413, Russia a

b

a Ural State Agrarian University, 75 Lenin Avenue, Chelyabinsk 454080, Russia South South Ural State University, 76 Lenin Avenue, Chelyabinsk 454080, Russia Russian Institute for Strategic Studies, 15-B Flotskaya str., Moscow 125413, Russia c South Ural State Agrarian University, 75 Lenin Avenue, Chelyabinsk 454080, Russia c

b

Abstract It is necessary to select the optimization criterion in order to determine operation parameters of transport and warehouse complexes. Abstract We developed a procedure for determining the optimal parameters for operation of the complexes. It includes methods of calculating thetooptimal of loading andinunloading mechanisms and parameters stations. The research and findings show complexes. that when It is necessary select theamount optimization criterion order to determine operation of transport warehouse calculating the optimal amount loading and the unloading it isofadvisable to take into account methods the ratio of We developed a procedure forofdetermining optimalmechanisms parameters and for stations operation the complexes. It includes intervals of the arrival loadingand andunloading unloading mechanisms and the standard one research unloadingfindings mechanism operation. In calculating the rolling optimalstock amount offor loading and duration stations.ofThe show that when order to determine the optimal of loading and unloading mechanisms and stations in warehouse wethe propose calculating the optimal amountamount of loading and unloading mechanisms and stations it is advisable to takecomplexes, into account ratio ofa cost-based the form offor minimum aggregate costsand fortheloading and unloading operations by transport intervals of criterion the rollinginstock arrival loading and unloading standard duration of one unloadingincurred mechanism operation.and In warehouse complexes the downtime rollingand stock in the course of loading and unloading operations incurredwe bypropose shippinga order to determine the and optimal amount of of loading unloading mechanisms and stations in warehouse complexes, organizations. It has in been the savingaggregate of the total costsforand losses and incurred by carriers and the terminalbytotransport organize and the cost-based criterion thefound form that of minimum costs loading unloading operations incurred unloading vehicles using twodowntime loaders atofone unloading is 23 %ofasloading compared the unloading at twoincurred unloading warehouseof complexes and the rolling stock station in the course andtounloading operations by stations. shipping organizations. It has been found that the saving of the total costs and losses incurred by carriers and the terminal to organize the © 2018 The Elsevier Ltd. unloading ofAuthors. vehicles Published using two by loaders at one unloading station is 23 % as compared to the unloading at two unloading stations. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Copyright © 2018 Elsevier Ltd. All rights reserved. Selection andAuthors. peer-review underby responsibility © 2018 The Published Elsevier Ltd.of the scientific committee of the EURO Mini Conference on "Advances in Selection and peer-review under responsibility of the scientific committee of the EURO Mini Conference on “Advances in Freight Freight Transportation and Logistics" This is an open access article under the(emc-ftl2018). CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Transportation and Logistics” (emc-ftl2018). Selection and peer-review under responsibility of the scientific committee of the EURO Mini Conference on "Advances in Keywords: transport and warehouse complexes; optimization; loading and unloading points and mechanisms. Freight Transportation and Logistics" (emc-ftl2018). Keywords: transport and warehouse complexes; optimization; loading and unloading points and mechanisms.

* Corresponding author. Tel.: +7-951-126-10-15; fax: +0-000-000-0000 . E-mail address: [email protected] * Corresponding author. Tel.: +7-951-126-10-15; fax: +0-000-000-0000 . 2352-1465 © 2018 The Authors. Published by Elsevier Ltd. E-mail address: [email protected] This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection peer-review under responsibility of the scientific 2352-1465and © 2018 The Authors. Published by Elsevier Ltd. committee of the EURO Mini Conference on "Advances in Freight Transportation and ThisLogistics" is an open(emc-ftl2018). access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the EURO Mini Conference on "Advances in Freight Transportation and Logistics" (emc-ftl2018). 2352-1465 Copyright  2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the EURO Mini Conference on “Advances in Freight Transportation and Logistics" (emc-ftl2018). 10.1016/j.trpro.2018.09.026

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1. Introduction An analysis of the studies by Naumov et al. (2015), Chao et al. (2017), Almetova et al. (2016) shows that to determine the operation parameters for transport and warehouse complexes, cost criteria of optimization are used as the local optimum which enables warehouse complexes to incur minimum costs for loading and unloading operations, but the aggregate losses of transport organizations, caused by rolling stock downtime in unloading operations are not taken into account [Selinka et al. (2016), Guan et al. (2009), Almetova et al. (2017), Liu et al. (2008), Sedláček (2017)]. The indicators of ROI (return of investments) and TCO (total cost of ownership), as well as the reduction of the cost of warehouse cargo processing [Grevtsov (2012)] were used as criteria of the efficiency of optimizing warehouse processes. The work by Nikolashin (2001) presents the model of determining optimum techno-technological standard-setting parameters of a supporting cargo processing and storage system. However, these procedures are mainly oriented toward the optimization of technological parameters of cargo processing. There is a method for assessing the effectiveness of a container terminal as an independent business entity based on two indicators - the cost of processing one container and the profitability of the terminal [Efremov (2005)]. These indicators do not take into account the economic performance of carriers, which, in terms of logistics, does not meet the system optimization requirements. Demin (2009) offers a methodology for calculating the number of stations, taking into account various factors, including the area of the acceptance-shipment site. However, the task of determining the optimal number of stations, taking into account the total costs for the downtime of cargo docks and cars in the analytical form was not solved, and the proposed iterative algorithm for obtaining a solution in the graphoanalytical form in practical conditions requires significant time and material resources to find an optimal solution, which is not entirely effective. Chislov (2009) takes the total reduced transportation costs for intranode carriages as a criterion of the optimization of the rational design and placement of elements of transport-technological and warehouse systems in industrialtransport nodes, but does not take into account the costs of transport companies and terminals caused by the downtime of machinery and equipment. From the viewpoint of the systematic approach and logistic principles of the organisation of transport and technological processes, the task of organising loading and unloading operations in transit terminals is to determine the productivity of loading and unloading complexes, at which the optimisation of the total effect will be ensured in the form of minimum economic losses for all participants in logistical processes: carriers of related modes of transport, owners of transport infrastructure, warehouse complexes, etc. [Assadipour et al. (2015), Huynh et al. (2008), Tsiulin et al. (2017), Faber et al. (2017), Ebben et al. (2005), Makarova et al. (2017)]. The problematic character of this situation is that, on the one hand, excessive unloading facilities lead to their downtime, a decrease in the efficiency of transport-warehouse complexes and a low return on investment in their creation. [Zabara et al. (2015), Kharchenko et al. (2006), Abad et al. (2005), Hesse et al. (2004)]. On the other hand, the shortage of mechanisms leads to the increase of rolling stock downtime [Sharamenko (2015), Yaxiong et al. (2010), Ballis et al. (2002)]. It undermines the operation efficiency of all transport process participants. As a result, the intensity of load transit flows through the links of a logistic chain. The existing contradictions necessitate further research in order to specify the optimization criterion when determining operational parameters of transport and warehouse complexes. Thus, the purpose of the study is to optimise the parameters of the operation of transport and warehouse complexes on the basis of developing a methodology for calculating the optimal number of loading and unloading mechanisms and stations, which ensures minimum aggregate work costs and non-productive downtime of loading and unloading complexes and loss of carriers in connection with the idle rolling stock under the appropriate operations. Thus, the research aims to optimize the parameters of transport and warehouse complexes operations on the basis of developing a methodology for calculating the optimal amount of loading and unloading mechanisms and points which would provide minimum aggregate losses. 2. Research methodology The amount of aggregate losses is defined as the sum of products of rolling stock downtime during loading and

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unloading, operating time of loading and unloading mechanisms, forced downtime of loading and unloading facilities and above-level downtime of rolling stock during loading and unloading which exceeds the planned operating time by the amount of operational costs [Javadi et al. (2014), Hofmann et al. (2010), Marko et al. (2012), Sierpiński (2018), Pypno et al. (2017)]. Taking into account the authors’ methods an objective function for proving the optimal parameters of transport and warehouse complexes has been developed based on the minimum aggregate cost criterion [Litomin et al. (2016), Luna et al. (2017), Ližbetin et al. (2015), Cao et al. (2008), Maknoon et al. (2016)]: Zo cyzd





F no kpj , no n , Z cyzd  no kp , no n   min

(1)

o is the optimal amount of loading and unloading mechanisms on one Z o cyzd is minimum aggregate costs, rubles; nkpj

o

point, units; nn is the optimal number of loading and unloading points, units. Efficiency and productivity of transport and warehouse complexes operations depend on the number of loading and unloading mechanisms for one vehicle on one loading and unloading point and the number of loading and unloading points on warehouse complexes. It was found that the choice of method for calculating the optimal operation criteria depends on the correlation of intervals of a rolling stock arrival for loading and unloading and its handling operation period. With the help of modeling three possible combinations of indices were brought out:  there is a continuous operation of both transport and warehouse complexes with one loading and unloading mechanism and a set flow of arriving rolling stock;  planned duration of rolling stock loading and unloading is less than its operation intervals;  planned duration of rolling stock unloading exceeds its operation intervals. For each case, we developed functions of total costs, on the basis of which, using the functional analysis methods, we determined the expressions for calculating the optimal number of loading and unloading mechanisms. Based on the theoretical studies, we developed the functions of total costs for the three cases mentioned above, from which we determined the optimum numbers of loading and unloading mechanisms. The value is set so that the cost reaches a minimum value. For the solution we used the methods of finding the extreme value of the objective function. Then, we differentiated expressions 2, 4, 6 along nkpj and setting to zero obtained the formulas for an optimal number of loading and unloading mechanisms at one station: Variant 1

Z cvz  Z ci  Z vi  Z zi  

Scitпl Svitnl nkpj t   S zinкрj ( tпl  пl )  nkpj nkpj nkpj

Scitпl  Svitnl  S zinkpjtпl  S zitпl nkpj

n о kpj 

S ci S zi

(2)

(3)

Z ci is costs due to downtime of a rolling stock in the course of loading and unloading operations inside the limits of the planned time for loading and unloading operations for all the time of downtime of one vehicle in the course of loading and unloading operations with account to the rate of loss (rub/h); Z vi is operational costs for loading and

unloading mechanism with account for the cost standard (rub/h); Z zi is costs due to forced downtime of each loading and unloading mechanism during the absence of a rolling stock, with account to the cost standard (rub/h); tnl – planned time for a vehicle being handled by one loading and unloading mechanism, h; S ci , S vi , S zi are cost value for the

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corresponding operations, rub. If the obtained value of the optimal number of loading and unloading mechanisms is not an integer value, it is necessary to round it up to an integer value upward or downward by the rule of minimum costs. The deviation of the optimum number of loading and unloading mechanisms to an integer value leads to an increase in costs with the optimum number of loading and unloading mechanisms at one station, so the choice of the direction of rounding should reduce the increase in costs to a minimum value. Variant 2

Z cvz  Z ci  Z vi  Z zi  

t Scitnl Svi tnl nkpj   S zinкрj ( I c  nl )  nkpj nkpj nkpj

Scitnl  Svitnl  S zinkpj I c  S zitnl nkpj

(4)

I c is the traffic flow interval, h.

S ci t nl S zi I c

n o kpj 

(5)

Variant 3

Z cvz  Z ci  Z vi  Z zi 

nkpj  nkpI Svitnl nkpj Scitnl    Svit рl nkpj  nkpI nkpj  nkpI nkpj

 t  t nl   Scitnl  Svt tnl   S zi nkpj  nkpI  nl   nkpI nkpj  n kpI  nkpj  nkpI   S zitnl nkpj  nkpI S zitnl nkpj  nkpI    nkpI nkpj  nkpI















(6)

S zitnl nkpj Scitnl  Svitnl   S zitnl nkpj  nkpI nkpI

nkpI is the number of loading and unloading mechanisms necessary to liquidate the queue during loading and unloading operations, units.





o nkpj   2nkpI 

1 2

Sci nkpI  2  2nkpI 2  4 nkpI   S 

zi



(7)

The optimal estimated amount of unloading facilities and stations may not be always realized in practice due to the restrictions to the simultaneous placement of the maximum permissible amount of unloading facilities at one station and the maximum permissible number of unloading stations in transport and warehouse complexes. The restrictions of the studied system are set for each variant of the ratios of the arrival intervals and the planned time of servicing the vehicles. The decision made taking into account the restrictions is considered to be rational, if significant losses of carriers and transport and warehouse complexes are possible. oI c If the obtained value nkpj is not an integer quantity, it is necessary to round it up to an integer value nkpj , upward

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oI c oI or downward by the rule of minimum costs. The deviation of nkpj to the value of nkpj from the optimal value nkpj oI oI leads to an increase in the costs Z cvzi at nkpj , therefore the choice of the rounding direction should reduce the growth

of Z cvj to a minimum value. For this purpose, we calculated additional variable costs connected with the downtime of vehicles under unloading,   c operation and the downtime of the unloading mechanisms Z cvzj and Z cvzj for the two nearest integer values nkpj

and n+c kpj obtained by rounding upward or downward, respectively. * c  The value nkpj is taken equal to the number of unloading mechanisms nkpj or n+c kpj , at which the total costs Z cvzj  and Z cvzj will be minimum. When choosing the final variant of the solution, it is necessary to check the fulfillment of the restriction on the *I '  nkp maximum possible number of unloading mechanisms at one unloading station: nkpj , units. *I ' If this condition is not met, the rational value of nkpj of unloading mechanisms is taken equal to nkp , i.e.: *I ' nkpj = nkp , units. *I ' > nkp If the restriction on the number of unloading mechanisms is not fulfilled: nkpj , it should be concluded that it is necessary to rebuild the unloading station by increasing the performance of the unloading means used and (or) reconstructing the unloading station to accommodate an additional number of unloading mechanisms. *II ' oII ' The rational number of unloading mechanisms nkpj in view of the restriction on nkp for this variant is: nkpj  nkp *II ' If this condition is not met, the rational value of nkpj of unloading mechanisms is taken equal to nkp , i.e.: *II nkpj = n'kp

If the restriction on the number of unloading mechanisms is not fulfilled, it can be concluded that it is necessary to rebuild the unloading station by increasing the performance of the unloading mechanisms used and (or) reconstructing the unloading station to accommodate an additional number of unloading mechanisms. c For the second case, if necessary, the integer value of the number of unloading devices nkpj is justified.

The integer value of the number of unloading devices is justified according to the rule of minimum costs, which is ' oIII ' compared to the restriction of nkp : nkpj  nkp . *III ' If this condition is not met, the rational value of nkpj of unloading mechanisms is taken equal to nkp , i.e.: oIII *III nkpj = n'kp when nkpj > n'kp .

' Taking into account the potential restriction of nkp of the maximum number of unloading mechanisms at one *I  III unloading station, the rational number of unloading mechanisms for all the cases nkp will be:

oI-III '  '  nkp *I-III nkp , at nkp nkp   oI-III oI-III '  nkp at nkp  nkp

(8)

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3. Results Fig. 1 shows the components and total costs for different variants of the ratio of the planned time of the vehicles arrival and their traffic intervals: the planned duration of unloading of rolling stock is equal to its traffic intervals; change in the costs in case of a loading and unloading time reserve; change in the costs when the planned duration of unloading of rolling stock is larger than its traffic intervals ( Z d is above-level downtime costs of a rolling stock in the course of loading and unloading operations that exceed its planned operational time for all the time of above-level downtime with account of standard cost (rub./h), Z zi is represents the costs due to the forced downtime of each loading and unloading mechanism in the absence of a rolling stock, taking into account the cost standards (rub./h).

Fig. 1. Change of costs in case (a) tnl  I c ; (b) tnl  I c ; (c) tnl  I c .

In case of queue additional points for loading and unloading are arranged:

nno 

nkpI n'kp

(9)

nkp' is maximum quantity of loading and unloading points, units. With account of feasible constraints on the maximum quantity of loading and unloading points on warehouse complexes, rational quantity of points will amount to: n , when nпo  nп ; nп*   пo o .  nп , when nп  nкр

nп* is rational quantity of points, units.

(10)

Thus, when determining optimal performance parameters, it is necessary to use cost criteria in the form of minimum aggregate costs of terminals for performing cargo handling and losses of carriers connected with the downtime of a rolling stock used for the appropriate operations. When calculating the optimal number of loading and unloading mechanisms and stations, it is necessary to take into account the ratio of the intervals for the arrival of vehicles for unloading (loading) and the duration of their servicing by one unloading facility. The use of the developed methods for optimizing the parameters of loading and unloading complexes of transit terminals was considered by the example of a terminal located in the Chelyabinsk region and carrying out distribution functions in several regions of the Urals and Siberia.

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The terminal operates day-and-night. The parameters of unloading operations include: average arrival rate of vehicles for unloading  = 50 units/h; average capacity of one vehicle q = 10 t; average number of cargo modules in one vehicle mq = 20 units; average time of mechanized unloading of one cargo module (euro pallets) by one unloading facility (loader) tcon = 2 min; number of unloading mechanisms at one unloading station for simultaneous unloading ' = 2 units; cost standard for the operation of one unloading facility S  = 2000 rub./h; cost standard of one vehicle nkp

of a forced downtime of an unloading facility, S z = 800 rub./h; loss rate due to the downtime of the vehicle under unloading S d = 1500 rub./h; penalty for an excess downtime of a vehicle under unloading S d = 2500 rub./h. If the restriction on the number of stations is not fulfilled, then the available capacities of the warehouse complex will not be sufficient for full servicing of vehicles that excludes the formation of an endless queue for unloading. In this case, it should be concluded that it is necessary to modernise the complex by increasing the productivity of the unloading facilities and (or) allocating the territory to accommodate additional unloading stations in the optimal quantity, at which the queue of vehicles waiting for unloading will be eliminated. The above methodical provisions of optimisation of the number of loading and unloading facilities and stations are considered on the example of discharging operations and, as a consequence, these solutions allow determining the optimal number of unloading facilities and stations. To optimise the number of loading facilities and stations, calculations are made in the same way with a single meaning substitution: instead of the planned time for discharging operations, the planned time for loading works is used, and instead of the interval of arrival of vehicles to the terminal for unloading, the interval of sending loaded vehicles from the terminal is used. Thus, cost criteria should be applied when determining the optimal operation parameters. It was found that, when average intensity values of vehicles arrival for loading and unloading amount to 50 units/h, one vehicle capacity amounts to 10 tons, and standard time of mechanical unloading of a europallet by one unloading mechanism amounts to 2 minutes, 2 unloading facilities are required on one unloading point for simultaneous loading and unloading of a vehicle. When using one loading mechanism, the average time of a vehicle unloading equals to the planned value. It was found that in case the planned time of rolling stock unloading exceeds the interval of their arrival, one loading and unloading point will not cope with on time unloading of all the arriving vehicles. To clear the queue on warehouse complexes it is necessary to use an additional point with one loading mechanism. The quantity of unloading facilities that would exclude queue of vehicles pending unloading will amount to 1.4 units, and the optimal quantity of unloading facilities on one point will amount to 1.6 units. With account of the constraints (10), the rational quantity of unloading facilities for operating on one unloading point will amount to 2 units. If there are two unloading points, there is no queue for unloading, as the traffic interval exceeds the planned time of loading and unloading. It was found that the savings of aggregate costs and losses incurred by carriers and a terminal for vehicles unloading with the help of two loaders on one unloading point in comparison with unloading on two unloading points amount to 23 %. This effect is due to reducing the downtime of unloading facilities pending the transport arrival. 4. Conclusion The study shows that adding extra loading and unloading mechanisms to a point reduces the planned time for loading and unloading operations, that in the first two cases leads to non-productive downtime of loading and unloading mechanisms and related losses of transport and warehouse complexes, and it also reduces the time of rolling stock being loaded and unloaded. Increasing the quantity of loading and unloading mechanisms in the third case allows eliminating above-level downtime of a rolling stock in queue for loading and unloading, and the administration of warehouse complexes has to pay the fine for all the above-level downtime to the vehicle owner. With account of the stated aggregate cost dependence on the quantity of loading and unloading mechanisms, there should be installed as many of them as to reduce to the minimum total operational costs, costs associated with nonproductive downtime of transport and warehouse complexes and losses of transport organizations.

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