Journal articles: 'Spare Capacity Allocation'

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Liu, Yu, David Tipper, and Korn Vajanapoom. "Spare Capacity Allocation in Two-Layer Networks." IEEE Journal on Selected Areas in Communications 25, no. 5 (June 2007): 974–86. http://dx.doi.org/10.1109/jsac.2007.070610.

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Yu Liu, D. Tipper, and P. Siripongwutikorn. "Approximating optimal spare capacity allocation by successive survivable routing." IEEE/ACM Transactions on Networking 13, no. 1 (February 2005): 198–211. http://dx.doi.org/10.1109/tnet.2004.842220.

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Shahriar, Nashid, Shihabur Rahman Chowdhury, Reaz Ahmed, Aimal Khan, Siavash Fathi, Raouf Boutaba, Jeebak Mitra, and Liu Liu. "Virtual Network Survivability Through Joint Spare Capacity Allocation and Embedding." IEEE Journal on Selected Areas in Communications 36, no. 3 (March 2018): 502–18. http://dx.doi.org/10.1109/jsac.2018.2815430.

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Liu, William, Krzysztof Pawlikowski, and Harsha Sirisena. "Algebraic connectivity metric for spare capacity allocation problem in survivable networks." Computer Communications 34, no. 12 (August 2011): 1425–35. http://dx.doi.org/10.1016/j.comcom.2010.12.012.

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Liu, Victor Yu, and David Tipper. "Spare capacity allocation using shared backup path protection for dual link failures." Computer Communications 36, no. 6 (March 2013): 666–77. http://dx.doi.org/10.1016/j.comcom.2012.09.007.

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Jordán, Tibor, and Ildikó Schlotter. "Parameterized complexity of spare capacity allocation and the multicost Steiner subgraph problem." Journal of Discrete Algorithms 30 (January 2015): 29–44. http://dx.doi.org/10.1016/j.jda.2014.11.005.

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Ho, Pin-Han, and H. T. Mouftah. "Framework of spare capacity re-allocation with S-SLSP for mesh WDM networks." Computer Networks 40, no. 1 (September 2002): 167–79. http://dx.doi.org/10.1016/s1389-1286(02)00272-4.

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Tridandapani, S., A. K. Somani, and U. R. Sandadi. "Low overhead multiprocessor allocation strategies exploiting system spare capacity for fault detection and location." IEEE Transactions on Computers 44, no. 7 (July 1995): 865–77. http://dx.doi.org/10.1109/12.392845.

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Harle, D., and S. Albarrak. "Spare capacity allocation and optimisation in a distributed GMPLS-based IP/WDM mesh network." Computer Communications 30, no. 16 (November 2007): 3085–95. http://dx.doi.org/10.1016/j.comcom.2007.05.057.

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Ahmad, Md Tanweer, and Sandeep Mondal. "Dynamic supplier selection approach for mining equipment company." Journal of Modelling in Management 14, no. 1 (February 11, 2019): 77–105. http://dx.doi.org/10.1108/jm2-04-2018-0046.

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PurposeThis paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.Design/methodology/approachAn integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.FindingsThe ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.Practical implicationsThis paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.Originality/valueIt provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

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Wang, Rui, Yicong Qin, and Hui Sun. "Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC." Computational Intelligence and Neuroscience 2021 (August 18, 2021): 1–16. http://dx.doi.org/10.1155/2021/4737700.

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With the increased demands of airlines, it is important to study the location selection strategy for spare parts central warehouse in order to improve the allocation capacity of spare parts maintenance resources and reduce the operating costs of airlines. Based on the M/M/s/∞/∞ multiservice desk model and Multi-Echelon Technique for Recoverable Item Control (METRIC) theory, this paper proposes a spare parts supply strategy based on the spare parts pool network and establishes a location selection model for spare parts central warehouse. The particle swarm optimization (PSO) algorithm is used to iteratively optimize the location for spare parts central warehouse and adjust the location area of the central warehouse combining transportation facilities and geographical environment factors. Finally, the paper compares the operating results for multiple airlines in pooling and off-pooling states and verifies the effectiveness of the spare parts supply model and the advantages of cost control for airlines.

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Siebert, Patrick, Mustapha Mouloua, Kendra Burns, Jennifer Marino, Lora Scagliola, Lelah Winters, Peter Hancock, and Dan Agliata. "The Effects of Telematics on Driver Distraction." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 22 (September 2002): 1868–70. http://dx.doi.org/10.1177/154193120204602219.

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This study used both cellular phones and analogue radio to measure driver distraction and workload in a low fidelity driving simulator. Thirty-four participants performed a simulated driving task while using either a cell phone or a radio in conjunction with a secondary task assessing their spare attentional capacity. The results showed that more lane deviations were made during the cell phone and radio tuning use than both of the pre-allocation and Post-allocation phases. The secondary task errors were also higher during both the cell phone and radio tuning allocation phase than the pre-allocation and post-allocation phases. These findings indicate the greater workload load levels associated with the use of telemetric devices. These findings have major implications for driver safety and telemetric systems design.

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Neal, Andrew, Michael A. West, and Malcolm G. Patterson. "Do Organizational Climate and Competitive Strategy Moderate the Relationship Between Human Resource Management and Productivity?" Journal of Management 31, no. 4 (August 2005): 492–512. http://dx.doi.org/10.1177/0149206304272188.

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This study examined whether the effectiveness of human resource management (HRM) practices is contingent on organizational climate and competitive strategy. The concepts of internal and external fit suggest that the positive relationship between HRM and subsequent productivity will be stronger for firms with a positive organizational climate and for firms using differentiation strategies. Resource allocation theories of motivation, on the other hand, predict that the relationship between HRM and productivity will be stronger for firms with a poor climate because employees working in these firms should have the greatest amount of spare capacity. The results supported the resource allocation argument.

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Kennington, Jeffery L., and Mark W. Lewis. "The Path Restoration Version of the Spare Capacity Allocation Problem with Modularity Restrictions: Models, Algorithms, and an Empirical Analysis." INFORMS Journal on Computing 13, no. 3 (August 2001): 181–90. http://dx.doi.org/10.1287/ijoc.13.3.181.12629.

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Koubàa, Mohamed, Maroua Bakri, Ammar Bouallègue, and Maurice Gagnaire. "QoT-aware elastic bandwidth allocation and spare capacity assignment in flexible island-based optical transport networks under shared risk link group constraints." Computer Networks 116 (April 2017): 111–40. http://dx.doi.org/10.1016/j.comnet.2017.02.005.

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Budiawan, Wiwik, Arfan Bachtiar, and Veronica Desy Afriyanti. "Evaluation of advertisement existence toward attention and understanding level vehicle driver." SHS Web of Conferences 49 (2018): 02019. http://dx.doi.org/10.1051/shsconf/20184902019.

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When driving on the road many things can draw attention of the main task for driving, for example advertisement. The success of an advertising depends on how well it was able to communicate with the target properly. Information processing consisting of the perception process, organizing, and remembering of receiving information. This study tries to assess four-wheel drive behaviour when he saw advertisement on the road using The Eye Tracking method to know Allocation Time of Visual Spare Capacity, Attention Level and Understanding Level driver’s. From 20 people who are respondents only 15 respondents have seen advertisement displayed and obtained research results that while driving, drivers have allocation of time of 6,52 second or 3,78 % of the whole long drive duration. With a small percentage, the attention of driver had low results seen from the perspective of eye integration for the advertisement. In this research also known that images and colour are easier to remember compared with the number of pictures displayed. So, the cognitive recommendation that can be given are the minimum distance between advertisement of 890 meters, Maximum element in advertisement contain 8 elements, Using the dark background in light coloured or otherwise, avoid several colours that hard to read if put together and Using Uppercase or Lowercase Font Style.

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Chen, Rui, Wen Hua Zeng, and Kai Ji Fan. "Research on Hadoop Greedy Scheduler Based on the Fair." Applied Mechanics and Materials 145 (December 2011): 460–64. http://dx.doi.org/10.4028/www.scientific.net/amm.145.460.

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Job scheduling technology is one of the Hadoop platform’s key technologies, whose main function is to control the execute sequence of job and the distribution of computing resources, which directly relates to the Hadoop platform’s overall performance and system resources, usage. However, the existing job scheduling algorithms such as FIFO Scheduler, Fair Scheduler and Capacity Scheduler all have some defects. To overcome theses defects, this paper proposed a new algorithm Hadoop Greedy Scheduler Based on the Fair (HGSF). Firstly, the job pools are sorted by priority from high to low; pools in the same priority are sorted by their minimum requirements. Then their minimum requirements are met in turn. If have spare computing resources, it will be assigned to the job pool which has the highest priority and the minimum difference between the ideal requirement and the minimum requirement. Finally, the algorithm uses delay allocation strategy to improve the localization of the data for computing tasks. The experimental results testified the effectiveness of the proposed algorithm.

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Chengot, Rishma, Jerry W. Knox, and Ian P. Holman. "Evaluating the Feasibility of Water Sharing as a Drought Risk Management Tool for Irrigated Agriculture." Sustainability 13, no. 3 (January 30, 2021): 1456. http://dx.doi.org/10.3390/su13031456.

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Droughts can exert significant pressure on regional water resources resulting in abstraction constraints for irrigated agriculture with consequences for productivity and revenue. While water trading can support more efficient water allocation, high transactional costs and delays in approvals often restrict its wider uptake among users. Collaborative water sharing is an alternative approach to formal water trading that has received much less regulatory and industry attention. This study assessed how the potential benefits of water sharing to reduce water resources risks in agriculture are affected by both drought severity and the spatial scale of water-sharing agreements. The research focused on an intensively farmed lowland catchment in Eastern England, a known hot-spot for irrigation intensity and recurrent abstraction pressures. The benefits of water sharing were modelled at four spatial scales: (i) individual licence (with no water sharing), (ii) tributary water sharing among small farmer groups (iii) sub-catchment and (iv) catchment scale. The benefits of water sharing were evaluated based on the modelled reductions in the probability of an irrigation deficit occurring (reducing drought risks) and reduced licensed ‘headroom’ (spare capacity redeployed for more equitable allocation). The potential benefits of water sharing were found to increase with scale, but its impact was limited at high levels of drought severity due to regulatory drought management controls. The broader implications for water sharing to mitigate drought impacts, the barriers to wider uptake and the environmental consequences are discussed.

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Hardie, Marie. "Vectors of technical innovation delivery by small and medium Australian construction firms." Construction Economics and Building 16, no. 3 (September 8, 2016): 59–70. http://dx.doi.org/10.5130/ajceb.v16i3.5158.

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Long-established Schumpeterian theory on innovation assumes that significant innovations are generated by large companies with ample spare resources. The allocation of time and money to speculative endeavours with unclear outcomes has often been regarded as beyond the scope of small and medium-sized enterprises (SMEs). As a result, authorities sometimes advise SMEs to concentrate on the adoption of existing innovative products and processes rather than the generation of new creative ideas. Despite this traditional wisdom, some very capable individuals actively choose to participate in the SME sector because the relative absence of internal bureaucratic processes and the capacity for agile response to changing circumstances. Ten case studies of significant technical innovations generated within construction SMEs were examined in the light of common themes identified through a literature review. The case studies were classified according to existing taxonomies of innovation. Content analysis was used to map the identified themes against the published material about the innovations from patent applications, company websites, trade literature and industry magazines. The findings indicate that SME innovation stems from several distinct motivations. These drivers of innovation can be described vectors. They inspire innovative solutions but the generated innovations also drive development towards solutions for other, quite different problems.

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Bolouri, S., A. Vafaeinejad, A. Alesheikh, and H. Aghamohammadi. "INVESTIGATING THE EFFECT OF CAPACITY CRITERION ON THE OPTIMAL ALLOCATION OF EMERGENCY FACILITIES IN GIS ENVIRONMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 211–17. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-211-2019.

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Abstract. Location-allocation analysis is one of the most GIS useful analysis, especially in allocating demands to facilities. One of these facilities is the fire stations, which the correct locations and optimal demand allocations to those have most importance. Each facility has a specific capacity that should be considered in locating the facilities and allocating the demand to those. In recent years, the use of unified models in solving allocation problems is too common because these models can solve a variety of problems, but in most of these models, the capacity criterion for facilities has been ignored. The present study tries to investigate the location-allocation problem of the fire stations with the aid of two Tabu and Genetic algorithms with the goal of maximizing the coverage using the (Vector Assignment Ordered Median Problem) VAOMP model, taking into account the capacity criterion and regardless of it. The results of using two algorithms in problem-solving show that the Genetic algorithm produces better quality solutions over a shorter time. Also, considering the capacity criterion that brings the problem closer to real-world space, in the study area, 59,640 demands will not be covered by any station within a 5-minute radius and will be highly vulnerable to potential hazards. Also, by adding 3 stations to the existing stations and re-allocating, the average of allocated demands with the help of Genetic was 93.39% and 92.74% for the Tabu algorithm. So it is necessary to consider the capacity of the facilities for optimal services.

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Bikker, Ingeborg A., Martijn R. K. Mes, Antoine Sauré, and Richard J. Boucherie. "ONLINE CAPACITY PLANNING FOR REHABILITATION TREATMENTS: AN APPROXIMATE DYNAMIC PROGRAMMING APPROACH." Probability in the Engineering and Informational Sciences 34, no. 3 (December 11, 2018): 381–405. http://dx.doi.org/10.1017/s0269964818000402.

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AbstractWe study an online capacity planning problem in which arriving patients require a series of appointments at several departments, within a certain access time target.This research is motivated by a study of rehabilitation planning practices at the Sint Maartenskliniek hospital (the Netherlands). In practice, the prescribed treatments and activities are typically booked starting in the first available week, leaving no space for urgent patients who require a series of appointments at a short notice. This leads to the rescheduling of appointments or long access times for urgent patients, which has a negative effect on the quality of care and on patient satisfaction.We propose an approach for allocating capacity to patients at the moment of their arrival, in such a way that the total number of requests booked within their corresponding access time targets is maximized. The model considers online decision making regarding multi-priority, multi-appointment, and multi-resource capacity allocation. We formulate this problem as a Markov decision process (MDP) that takes into account the current patient schedule, and future arrivals. We develop an approximate dynamic programming (ADP) algorithm to obtain approximate optimal capacity allocation policies. We provide insights into the characteristics of the optimal policies and evaluate the performance of the resulting policies using simulation.

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SOHN, EUNJU, and CHARLES KNESSL. "On a storage allocation model with finite capacity." European Journal of Applied Mathematics 27, no. 5 (February 17, 2016): 738–55. http://dx.doi.org/10.1017/s0956792516000048.

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We consider a storage allocation model with a finite number of storage spaces. There are m primary spaces that are ranked {1,2,. . .,m} and R secondary spaces ranked {m + 1, m + 2,. . .,m + R}. Items arrive according to a Poisson process, occupy a space for a random exponentially distributed time, and an arriving item takes the lowest ranked available space. Letting N1 and N2 denote the numbers of occupied primary and secondary spaces, we study the joint distribution Prob[N1 = k, N2 = r] in the steady state. The joint process (N1, N2) behaves as a random walk in a lattice rectangle. We shall obtain explicit expressions for the distribution of (N1, N2), as well as the marginal distribution of N2. We also give some numerical studies to illustrate the qualitative behaviors of the distribution(s). The main contribution is to study the effects of a finite secondary capacity R, whereas previous studies had R = ∞.

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Gu, Yebo, Bowen Huang, and Zhilu Wu. "Power Allocation for Secrecy-Capacity-Optimization-Artificial-Noise Secure MIMO Precoding Systems under Perfect and Imperfect Channel State Information." Applied Sciences 11, no. 10 (May 17, 2021): 4558. http://dx.doi.org/10.3390/app11104558.

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In this paper, we consider the physical layer security problem of the wireless communication system. For the multiple-input, multiple-output (MIMO) wireless communication system, secrecy capacity optimization artificial noise (SCO−AN) is introduced and studied. Unlike its traditional counterpart, SCO−AN is an artificial noise located in the range space of the channel state information space and thus results in a significant increase in the secrecy capacity. Due to the limitation of transmission power, making rational use of this power is crucial to effectively increase the secrecy capacity. Hence, in this paper, the objective function of transmission power allocation is constructed. We also consider the imperfect channel estimation in the power allocation problems. In traditional AN research conducted in the past, the expression of the imperfect channel estimation effect was left unknown. Still, the extent to which the channel estimation error impacts the accuracy of secrecy capacity computation is not negligible. We derive the expression of channel estimation error for least square (LS) and minimum mean squared error (MMSE) channel estimation. The objective function for transmission power allocation is non-convex. That is, the traditional gradient method cannot be used to solve this non-convex optimization problem of power allocation. An improved sequence quadratic program (ISQP) is therefore applied to solve this optimization problem. The numerical result shows that the ISQP is better than other algorithms, and the power allocation as derived from ISQP significantly increases secrecy capacity.

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Sohn, Eunju, and Charles Knessl. "Asymptotic Analysis of a Storage Allocation Model with Finite Capacity: Joint Distribution." Advances in Operations Research 2016 (2016): 1–56. http://dx.doi.org/10.1155/2016/1925827.

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We consider a storage allocation model with a finite number of storage spaces. There aremprimary spaces andRsecondary spaces. All of them are numbered and ranked. Customers arrive according to a Poisson process and occupy a space for an exponentially distributed time period, and a new arrival takes the lowest ranked available space. We letN1andN2denote the numbers of occupied primary and secondary spaces and study the joint distributionProb[N1=k,N2=r]in the steady state. The joint process(N1,N2)behaves as a random walk in a lattice rectangle. We study the problem asymptotically as the Poisson arrival rateλbecomes large, and the storage capacitiesmandRare scaled to be commensurably large. We use a singular perturbation analysis to approximate the forward Kolmogorov equation(s) satisfied by the joint distribution.

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Shah, Bhavin, and Vivek Khanzode. "Designing a lean storage allocation policy for non-uniform unit loads in a forward-reserve model." Journal of Enterprise Information Management 31, no. 1 (February 12, 2018): 112–45. http://dx.doi.org/10.1108/jeim-01-2017-0018.

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Purpose The contemporary e-tailing marketplace insists that distribution centers are playing the roles of both wholesalers and retailers which require different storage-handling load sizes due to different product variants. To fulfill piecewise retail orders, a separate small size-fast pick area is design called “forward buffer” wherein pallets are allocated from reserve area. Due to non-uniform pallets, the static allocation policy diminishes forward space utilization and also, more than practically required buffer size has been identified as wastage. Thus, dynamic storage allocation policy is required to design for reducing storage wastage and improving throughput considering non-uniform unit load sizes. The purpose of this paper is to model such policy and develop an e-decision support system assisting enterprise practitioners with real-time decision making. Design/methodology/approach The research method is developed as a dynamic storage allocation policy and mathematical modeled as knapsack-based heuristics. The execution procedure of policy is explained as an example and tested with case-specific data. The developed model is implemented as a web-based support system and tested with rational data instances, as well as overcoming prejudices against single case findings. Findings The provided model considers variable size storage-handling unit loads and recommends number of pallets allocations in forward area reducing storage wastes. The algorithm searches and suggests the “just-right” amount of allocations for each product balancing existing forward capacity. It also helps to determine “lean buffer” size for forward area ensuring desired throughput. Sensitivity and buffer performance analysis is carried out for Poisson distributed data sets followed by research synthesis. Practical implications Warehouse practitioners can use this model ensuring a desired throughput level with least forward storage wastages. The model driven e-decision support system (DSS) helps for effective real-time decision making under complicated business scenarios wherein products are having different physical dimensions. It assists the researchers who would like to explore the emerging field of “lean” adoption in enterprise information and retail-distribution management. Originality/value The paper provides an inventive approach endorsing lean thinking in storage allocation policy design for a forward-reserve model. Also, the developed methodology incorporating features of e-DSS along with quantitative modeling is an inimitable research contribution justifying rational data support.

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Greve, Gabriel H., Kenneth M. Hopkinson, and Gary B. Lamont. "Evolutionary sensor allocation for the Space Surveillance Network." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 15, no. 3 (July 21, 2017): 303–22. http://dx.doi.org/10.1177/1548512917712614.

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The congested exosphere continues to contain more satellites and debris, raising the potential for destructive collisions. The Special Perturbations (SP) Tasker algorithm currently assigns the ground sensors tasks to track object locations. Accurate locations help avoid collisions. However, the SP Tasker ignores priority, which is the satellite’s importance factor. This article introduces the Evolutionary Algorithm Tasker (EAT) to solve the Satellite Sensor Allocation Problem (SSAP), which is a hybrid Evolutionary Strategy and Genetic Algorithm concept including specific techniques to explore the solution space and exploit the best solutions found. This approach goes beyond the current method, which does not include priority and other methods from the literature that have been applied to small-scale simulations. The SSAP model implementation extends Multi-Objective Evolutionary Algorithms (MOEAs) from the literature while accounting for priorities. Multiple real-world factors are considered, including each sensor’s field-of-view, the orbital opportunities to track a satellite, the capacity of the sensor, and the relative priority of the satellites. The single objective EAT is statistically compared to the SP Tasker algorithm. Simulations show that both the EAT and MOEA approaches effectively use priority in the core tasking algorithms to ensure that higher priority satellites are tracked.

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Zhang, Pengju, Wenping Ge, Yongxing Zhang, Mengyao Gao, and Gecheng Zhang. "Energy Efficiency and User Capacity Optimization of Cognitive MIMO Systems Via the SCMA-Based Nonorthogonal Time Slot Allocation." Symmetry 12, no. 7 (July 7, 2020): 1136. http://dx.doi.org/10.3390/sym12071136.

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This paper investigates the energy-efficient communications and user capacity in the cognitive multiple input multiple output (MIMO) symmetric system of underlay mode. The advantage of the improved energy efficiency provided by the orthogonal slot allocation for time division multiple access (TDMA) has a side effect of restricting the number of users accessing the system. To tackle the above problem, this paper proposes a nonorthogonal time resource allocation method with sparse code multiple access (SCMA), which allows one to convert the orthogonal slot units of TDMA into non-orthogonal shared slot units for multiple secondary users (SUs). The method of adding virtual users is adopted, wherein each SU is treated as multiple SUs who occupy a shared unit, to facilitate the packet access. Finally, the greedy algorithm is applied to optimize the time slot allocation of unoccupied shared slot units. The simulation results show that SCMA-based nonorthogonal slot allocation can reduce not only the energy consumption by nearly 40%, but also the average power interference from SUs to primary users by nearly 2 dB if their number is relatively high. Moreover, in the case of satisfying the rate requirement of the users, the system user capacity increased by more than 50%.

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Qi, Chenhao, Arumugam Nallanathan, and Lenan Wu. "Joint optimisation of secret key capacity and sparse channel estimation based on pilot power allocation." Electronics Letters 51, no. 13 (June 2015): 1033–35. http://dx.doi.org/10.1049/el.2014.4078.

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Li, Yuanhang, Jinlin Wang, and Rui Han. "An On-Path Caching Scheme Based on the Expected Number of Copies in Information-Centric Networks." Electronics 9, no. 10 (October 17, 2020): 1705. http://dx.doi.org/10.3390/electronics9101705.

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The Information-Centric Network (ICN) is one of the most influential future network architectures and in-network caching in ICN brings some helpful features, such as low latency and mobility support. How to allocate cache capacity and place content properly will greatly influence the performance of ICN. This paper focuses on the cache allocation problem and content placement problem under the given cache space budget. Firstly, a lightweight allocation method utilizing information of both topology and content popularity is proposed, to allocate cache space and get the expected number of copies of popular content. The expected number of copies represents the number of content copies placed in the topology. Then, an on-path caching scheme based on the expected number of copies is proposed to handle the content placement problem. In the cache allocation scenario, the lightweight allocation method performs better than other baseline methods. In the content placement scenario, Leave Copy Down (LCD) based on the expected number of copies performs the second-best and is very close to Optimal Content Placement (OCP).

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Hsieh, Chi-Kai, Kun-Lin Chan, and Feng-Tsun Chien. "Energy-Efficient Power Allocation and User Association in Heterogeneous Networks with Deep Reinforcement Learning." Applied Sciences 11, no. 9 (April 30, 2021): 4135. http://dx.doi.org/10.3390/app11094135.

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This paper studies the problem of joint power allocation and user association in wireless heterogeneous networks (HetNets) with a deep reinforcement learning (DRL)-based approach. This is a challenging problem since the action space is hybrid, consisting of continuous actions (power allocation) and discrete actions (device association). Instead of quantizing the continuous space (i.e., possible values of powers) into a set of discrete alternatives and applying traditional deep reinforcement approaches such as deep Q learning, we propose working on the hybrid space directly by using the novel parameterized deep Q-network (P-DQN) to update the learning policy and maximize the average cumulative reward. Furthermore, we incorporate the constraints of limited wireless backhaul capacity and the quality-of-service (QoS) of each user equipment (UE) into the learning process. Simulation results show that the proposed P-DQN outperforms the traditional approaches, such as the DQN and distance-based association, in terms of energy efficiency while satisfying the QoS and backhaul capacity constraints. The improvement in the energy efficiency of the proposed P-DQN on average may reach 77.6% and 140.6% over the traditional DQN and distance-based association approaches, respectively, in a HetNet with three SBS and five UEs.

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Yang, Zhong-Zhen, Gang Chen, and Dong-Ping Song. "Integrating truck arrival management into tactical operation planning at container terminals." Polish Maritime Research 20, Special-Issue (July 1, 2013): 32–46. http://dx.doi.org/10.2478/pomr-2013-0025.

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Abstract Truck arrival management (TAM) has been recognized as an effective solution to alleviate the gate congestion at container terminals. To further utilize TAM in improving the overall terminal performance, this study integrates TAM with the other terminal operations at a tactical level. An integrated planning model and a sequential planning model are presented to coordinate the major terminal planning activities, including quayside berth allocation, yard storage space allocation and TAM. A heuristic-based genetic algorithm is developed to solve the models. A range of numerical examinations are performed to compare two planning models. The result shows that: the integrated model can improve the terminal performance significantly from the sequential model alone, particularly when the gate capacity and the yard capacity are relatively low; whereas the sequential model is more efficient than the integrated model in terms of computational time.

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Ibrahim, Ahmed, A. Al-Awamry Al-Awamry, and Ashraf Shawky Mohra. "Managing the Interference for Down-Link in LTE Using Fractional Frequency Reuse." Indonesian Journal of Science and Technology 5, no. 3 (December 1, 2020): 440–55. http://dx.doi.org/10.17509/ijost.v5i3.25636.

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Long Term Evolution has developed a new radio technology called femtocell or Femto Base station, which is well-suited to improve cellular network capacity and mobile coverage to indoor user's areas. Providing additional capacity and coverage expansion through FBSs could lead to large interference in a cellular radio communication network. In this paper, we proposed an efficient resource allocation scheme based on Fraction Frequency Reuse (FFR) for interference mitigation, where the entire spectrum is shared among network entities. FFR mechanism aims to reduce co-tier and cross-tier downlink interferences by allocating non-overlapping sets of bands to the user equipment at different geographic locations. The main purpose of this work is to compare two main types of FFR schemes, respectively, Strict FFR and Soft Frequency Reuse with the proposed scheme. The three types of FFR schemes were explained and evaluated with Monte-Carlo simulation based on some performance metrics, namely, sum-rate, spectral efficiency, and outage probability. Simulation results showed that the impacts of the proposed scheme are significantly high in comparison with two other methods. The proposed scheme proved to enhance spectral efficiency, reduced the outage probability, and increased the sum rate for all the users.

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Guo, Jingni, Junxiang Xu, Zhenggang He, and Wei Liao. "Simulation Study on Cascading Failure of Multimodal Transport Network." Journal of Advanced Transportation 2020 (November 30, 2020): 1–9. http://dx.doi.org/10.1155/2020/3976910.

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Cascading failure in multimodal transport network may cause huge economic loss and social impact, which has gradually attracted public attention. In view of the coupling effect of nodes in multimodal transport network and the higher complexity of cascading failure process, the concepts of node correlation degree and node cooperation degree are proposed to characterize the characteristics of the network, and a logit model is introduced to calculate the initial load of nodes. In the case of ignoring network interruption, we propose two load redistribution methods: local allocation and global-local allocation. Taking the multimodal transport network in Sichuan–Tibet region of China as an example, the cascading failure effect of multimodal transport network in Sichuan–Tibet region is quantified by sensitivity analysis. The results show that when the load of the multimodal transport network in Sichuan–Tibet region exceeds the maximum capacity but does not exceed 150%∼170% of the network capacity, the network can still operate normally. In addition, the nodes in the multimodal transport network should have 0.3∼0.5 scalable space. In the cascading failure control method, load redistribution based on global-local allocation can minimize the impact of node overload.

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Holguín-Veras, José, and Sergio Jara-Díaz. "Preliminary Insights into Optimal Pricing and Space Allocation at Intermodal Terminals with Elastic Arrivals and Capacity Constraint." Networks and Spatial Economics 6, no. 1 (March 2006): 25–38. http://dx.doi.org/10.1007/s11067-006-7683-6.

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Chen, Jin, Changsong Chen, and Shanxu Duan. "Cooperative Optimization of Electric Vehicles and Renewable Energy Resources in a Regional Multi-Microgrid System." Applied Sciences 9, no. 11 (May 31, 2019): 2267. http://dx.doi.org/10.3390/app9112267.

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By integrating renewable energy sources (RESs) with electric vehicles (EVs) in microgrids, we are able to reduce carbon emissions as well as alleviate the dependence on fossil fuels. In order to improve the economy of an integrated system and fully exploit the potentiality of EVs’ mobile energy storage while achieving a reasonable configuration of RESs, a cooperative optimization method is proposed to cooperatively optimize the economic dispatching and capacity allocation of both RESs and EVs in the context of a regional multi-microgrid system. An across-time-and-space energy transmission (ATSET) of the EVs was considered, and the impact of ATSET of EVs on economic dispatching and capacity allocation of multi-microgrid system was analyzed. In order to overcome the difficulty of finding the global optimum of the non-smooth total cost function, an improved particle swarm optimization (IPSO) algorithm was used to solve the cooperative optimization problem. Case studies were performed, and the simulation results show that the proposed cooperative optimization method can significantly decrease the total cost of a multi-microgrid system.

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Ali, A. A., C. Xu, A. Rogers, R. A. Fisher, S. D. Wullschleger, E. C. Massoud, J. A. Vrugt, et al. "A global scale mechanistic model of photosynthetic capacity (LUNA V1.0)." Geoscientific Model Development 9, no. 2 (February 12, 2016): 587–606. http://dx.doi.org/10.5194/gmd-9-587-2016.

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Abstract. Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., Vc, max25) and the maximum electron transport rate (i.e., Jmax25) at a reference temperature (generally 25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ∼ 55 % of the global variation in observed values of Vc, max25 and ∼ 65 % of the variation in the observed values of Jmax25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of Vc, max25 are most affected in high-latitude regions under future climates. ESMs that relate the values of Vc, max25 or Jmax25 to plant functional types only are likely to substantially overestimate future global photosynthesis.

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Rodrigues, Edson, Eduardo Cerqueira, Denis Rosário, and Helder Oliveira. "Hybrid Routing, Modulation, Spectrum and Core Allocation Based on Mapping Scheme." Sensors 20, no. 21 (November 9, 2020): 6393. http://dx.doi.org/10.3390/s20216393.

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With the persistently growing popularity of internet traffic, telecom operators are forced to provide high-capacity, cost-efficient, and performance-adaptive connectivity solutions to fulfill the requirements and increase their returns. However, optical networks that make up the core of the Internet gradually reached physical transmission limits. In an attempt to provide new solutions emerged, the Space-Division Multiplexing Elastic Optical Network emerged as one of the best ways to deal with the network depletion. However, it is necessary to establish lightpaths using routing, modulation, spectrum, and core allocation (RMSCA) algorithms to establish connections in these networks. This article proposes a crosstalk-aware RMSCA algorithm that uses a multi-path and mapping scheme for improving resource allocation. The results show that the proposed algorithm decreases the blocking ratio by up to four orders of magnitude compared with other RMSCA algorithms in the literature.

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BAYEFSKY, MICHELLE J., and BENJAMIN E. BERKMAN. "The Ethics of Allocating Uterine Transplants." Cambridge Quarterly of Healthcare Ethics 25, no. 3 (February 11, 2016): 350–65. http://dx.doi.org/10.1017/s0963180115000687.

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Abstract:In September 2014, a healthy male child was born in Sweden following a successful uterine transplantation (UTx). The event brought hope to many women without functional uteruses around the world. Having a child with a transplanted uterus is now possible, and as knowledge of the procedure proliferates and interest in UTx grows, it is important to begin thinking about how a scarce supply of uteruses will be allocated. This article represents a first discussion of the range of factors that must be considered in answering the allocation question. The primary issues addressed are (1) the motivation to seek treatment, (2) allocation by age, (3) child-rearing capacity, and (4) the amount of infertility treatment required. A set of eligibility and ranking criteria are presented. These criteria are not exhaustive but are intended to spark discussion about how uteruses can be allocated in a just manner.

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Ali, Aamir, Muhammad Usman Keerio, and Noor Hussain Mugheri. "Constrained Composite Differential Evolution Search for Optimal Site and Size of Distributed Generation Along with Reconfiguration in Radial Distribution Network." Mehran University Research Journal of Engineering and Technology 39, no. 4 (October 1, 2020): 705–18. http://dx.doi.org/10.22581/muet1982.2004.03.

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This paper proposed a novel method to find the Optimal Feeder Reconfiguration (OFR) of radial distribution network along with optimal site and size of Distributed Generation (DG) with an objective of power loss reduction. OFR and DG allocation problems are highly non-linear and complex optimization problems, complexity of problem is further increased with the addition of distribution operation constraints. In the last two decades, Evolutionary Algorithms (EAs) have been implemented successfully to find the OFR and DG allocation considering different objective functions. However, search space adopted by EAs are unconstrained, therefore numerous methodologies are adapted to discard infeasible solutions. The penalty approach is most widely used in the literature, it requires appropriate selection of penalty parameters using a tedious trial and error method. In this paper, a new EA Constrained Composite Differential Evolution (C2oDE) is proposed find optimal capacity and site of DG along with reconfiguration problem. In the proposed algorithms three trial vectors are generated to strike balance among exploration and exploitation. Furthermore, to find the feasible solutions in the decision space two most widely used constraint handling techniques that include feasibility rule and ɛ-constrained method are added to select the trail vector and individuals respectively for the next generation. Proposed C2oDE method has been validated by considering IEEE 33-bus, 69-bus and 119-bus distribution networks at five different cases. Simulation results obtained shows better performance of proposed method against the most recent literature to find both OFR and DG allocation

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Fröberg, Lars, Anette Baur, and Bruno Baur. "Field study on the regenerative capacity of three calcicolous lichen species damaged by snail grazing." Lichenologist 38, no. 5 (August 22, 2006): 491–93. http://dx.doi.org/10.1017/s0024282906005469.

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Lichen growth and regeneration depend on the net photosynthetic production, the lateral allocation of products, on abiotic factors, competition and herbivory, and may therefore vary both in space and time (Hill 1981). Herbivores cause different damage to lichens in response to different thallus structure (surface toughness) and growth form, presence/absence of secondary compounds, and due to herbivore-specific differences in feeding (Lawrey 1984; Fröberg et al. 1993; Baur et al. 1994; Hesbacher et al. 1995). Regeneration of artificially damaged lichen tissue has been investigated in detail, for example in Xanthoria parietina (L.) Th. Fr. (Honegger 1996; Honegger et al. 1996). However, quantitative assessments of the regenerative capacity of thalli damaged by herbivores are so far lacking. Damage to lichens by grazing gastropods is made by highly specialized radulae and can therefore not be imitated by any mechanical treatment (Baur et al. 2000). Herbivory by snails also involves the production of saliva and mucus, which both could affect lichen regeneration.

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Concha, Cristobal, and Peter Doerner. "The impact of the rhizobia–legume symbiosis on host root system architecture." Journal of Experimental Botany 71, no. 13 (April 27, 2020): 3902–21. http://dx.doi.org/10.1093/jxb/eraa198.

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Abstract Legumes form symbioses with rhizobia to fix N2 in root nodules to supplement their nitrogen (N) requirements. Many studies have shown how symbioses affect the shoot, but far less is understood about how they modify root development and root system architecture (RSA). RSA is the distribution of roots in space and over time. RSA reflects host resource allocation into below-ground organs and patterns of host resource foraging underpinning its resource acquisition capacity. Recent studies have revealed a more comprehensive relationship between hosts and symbionts: the latter can affect host resource acquisition for phosphate and iron, and the symbiont’s production of plant growth regulators can enhance host resource flux and abundance. We review the current understanding of the effects of rhizobia–legume symbioses on legume root systems. We focus on resource acquisition and allocation within the host to conceptualize the effect of symbioses on RSA, and highlight opportunities for new directions of research.

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Ji, Xuechun, Maoxian Zhao, Mingyu Zhai, and Qingxi Wu. "Query Execution Optimization in Spark SQL." Scientific Programming 2020 (February 7, 2020): 1–12. http://dx.doi.org/10.1155/2020/6364752.

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Spark SQL is a big data processing tool for structured data query and analysis. However, due to the execution of Spark SQL, there are multiple times to write intermediate data to the disk, which reduces the execution efficiency of Spark SQL. Targeting on the existing issues, we design and implement an intermediate data cache layer between the underlying file system and the upper Spark core to reduce the cost of random disk I/O. By using the query pre-analysis module, we can dynamically adjust the capacity of cache layer for different queries. And the allocation module can allocate proper memory for each node in cluster. According to the sharing of the intermediate data in the Spark SQL workflow, this paper proposes a cost-based correlation merging algorithm, which can effectively reduce the cost of reading and writing redundant data. This paper develops the SSO (Spark SQL Optimizer) module and integrates it into the original Spark system to achieve the above functions. This paper compares the query performance with the existing Spark SQL by experiment data generated by TPC-H tool. The experimental results show that the SSO module can effectively improve the query efficiency, reduce the disk I/O cost and make full use of the cluster memory resources.

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Su, Xichao, Wei Han, Yu Wu, Yong Zhang, and Jie Liu. "A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations." Complexity 2018 (November 1, 2018): 1–38. http://dx.doi.org/10.1155/2018/6932985.

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The operations on the aircraft carrier flight deck are carried out in a time-critical and resource-constrained environment with uncertainty, and it is of great significance to optimize the makespan and obtain a robust schedule and resource allocation plan for a greater sortie generation capacity and better operational management of an aircraft carrier. In this paper, a proactive robust optimization method for flight deck scheduling with stochastic operation durations is proposed. Firstly, an operation on node-flow (OONF) network is adopted to model the precedence relationships of multi-aircraft operations, and resource constraints categorized into personnel, support equipment, workstation space, and supply resource are taken into consideration. On this basis, a mathematical model of the robust scheduling problem for flight deck operation (RSPFDO) is established, and the goal is to maximize the probability of completing within the limitative makespan (PCLM) and minimize the weighted sum of expected makespan and variance of makespan (IRM). Then, in terms of proactive planning, both serial and parallel schedule generation schemes for baseline schedule and robust personnel allocation scheme and equipment allocation adjustment scheme for resource allocation are designed. In terms of executing schedules, an RSPFDO-oriented preconstraint scheduling policy (CPC) is proposed. To optimize the baseline schedule and resource allocation, a hybrid teaching-learning-based optimization (HTLBO) algorithm is designed which integrates differential evolution operators, peak crossover operator, and learning-automata-based adaptive variable neighborhood search strategy. Simulation results shows that the HTLBO algorithm outperforms both some other state-of-the-art algorithms for deterministic cases and some existing algorithms for stochastic project scheduling, and the robustness of the flight deck operations can be improved with the proposed resource allocation schemes and CPC policy.

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Gao, Hui, Shuijing Zhai, Zhigao Sun, Juan Liu, and Chuan Tong. "Differences in biomass and silica content in typical plant communities with ecotones in the Min River estuary of southeast China." PeerJ 7 (July 22, 2019): e7218. http://dx.doi.org/10.7717/peerj.7218.

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Silica (Si) is a basic nutrient requirement for many aquatic organisms and its biogeochemical cycle plays an important role in estuarine coastal ecosystems. However, little is known about the role Si plays during plant–plant interactive processes in the marsh ecosystems. Here, variations in biomass, biogenic silica (BSi) content, and available Si content of Cyperus malaccensis-dominated marshes, Phragmites australis-dominated marshes, and their ecotonal marshes were studied in the Shanyutan marsh in the Min River estuary, China. Results showed that C. malaccensis and P. australis biomass in ecotones was lower than those in typical communities by 46.4% and 46.3%, respectively. BSi content in aboveground organs of C. malaccensis and culms and roots of P. australis was lower in ecotones than in typical communities, whereas BSi content in other organs showed the opposite trend. Biomass allocation in C. malaccensis and P. australis roots in ecotones was higher by 56.9% and 19.5%, respectively, and BSi stock in C. malaccensis and P. australis roots was higher than that in typical communities by 120.9% and 18.9%, respectively. Available Si content in ecotonal marsh soils was 12.6% greater than that in typical communities. Thus, the two plant species may use different strategies for Si accumulation and allocation in ecotones to adapt to the competitive environment. P. australis may expand primarily via occupation of wider aboveground space, thereby increasing the Si accumulation capacity in aboveground organs. Meanwhile, C. malaccensis may increase the Si allocation capacity of its roots to withstand the pressure from P. australis. This study will provide new insights into marsh plant competition from the perspective of Si, which can also benefit plant management in marsh ecosystems.

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Munjulury, Raghu Chaitanya, Ingo Staack, Adrián Sabaté López, and Petter Krus. "Knowledge-based aircraft fuel system integration." Aircraft Engineering and Aerospace Technology 90, no. 7 (October 1, 2018): 1128–35. http://dx.doi.org/10.1108/aeat-01-2017-0046.

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Purpose This paper aims to present a knowledge-based fuel system, implementation and application, oriented towards its use in aircraft conceptual design. Design/methodology/approach Methodology and software tools oriented to knowledge-based engineering applications (MOKA) is used as a foundation for the implementation and integration of fuel systems. Findings Including fuel systems earlier in the design process creates an opportunity to optimize it and obtain better solutions by allocating suitable locations in an aircraft, thereby reflecting on the centre of gravity of the aircraft. Research limitations/implications All geometries are symbolic, representing a space allocation inside the aircraft for the fuel system. A realistic representation of the real components could be realized in detail design. Practical implications Fuel weight is a significant part of take-off weight and decisive in aircraft sizing and range estimations. The three-dimensional geometry provides a better estimation of the volume that is available to allocate the necessary entities. It also provides fast measures for weight and balance, fuel capacity, relative tank positions and a first estimation of piping length. Originality/value Fuel systems appear early in the design process, as they are involved in several first estimations. By using a knowledge-based engineering approach, several alternatives can be visualized and estimated in the conceptual design process. Furthermore, using the weights and centre of gravity at different angles of pitch and roll of each fuel tank, the aircraft could be optimized for handling qualities by using automatically generated system simulation models.

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Paban Panda, Patita, and Sudhansu Sekhar Das. "A Hybrid Technique for Smart Parking Management System in a Smart City." International Journal of Engineering & Technology 7, no. 4.15 (October 7, 2018): 286. http://dx.doi.org/10.14419/ijet.v7i4.15.23009.

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Considering the urban environment, we proposed a new model “Parking Management System”. The complete model provides you the basic features of the parking system. The system designates an exact parking slot for the driver. On the basis of user requirement, it includes the proximity to destination and the cost of parking. The capacity of overall parking is utilized efficiently. The system approach solves the problem at individual decisions in a time driven sequence. This is the most favorable solution based on the allocation on present state affair and subject to the arbitrary incidents such as the request of the new user and availability of the parking space. At the next decision point, the allocation is updated ensuring that there is no conflicts in the resource reservation and the assignment of resource have the higher cost than the current cost of function value. The proposed system enables users to find out the free parking space on the cost on new performance metrics to calculate the cost of user parking under the consideration of distance and the total no of free places. The system show that the algorithm helps improves the probability of successful parking and the user waiting time is minimized. The proposed system is implemented by us in the real world successfully.

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Koudouridis, Georgios P., and Pablo Soldati. "Trading off Network Density with Frequency Spectrum for Resource Optimization in 5G Ultra-Dense Networks." Technologies 6, no. 4 (December 1, 2018): 114. http://dx.doi.org/10.3390/technologies6040114.

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To effectively increase the capacity in 5G wireless networks requires more spectrum and denser network deployments. However, due to the increasing network density, the coordination of network and spectrum management becomes a challenging task both within a single operator’s network and among multiple operators’ networks. In this article, we develop new radio resource management (RRM) algorithms for adapting the frequency spectrum and the density of active access nodes in 5G ultra-dense networks (UDNs) to the traffic load and the user density in different geographical areas of the network. To this end, we formulate a network optimization problem where the allocation of spectrum bandwidth and the density of active access nodes are optimized to minimize a joint cost function, and we exploit Lagrange duality techniques to develop provably optimal network-scheduling algorithms. In particular, we develop density algorithms for two application scenarios. The first scenario solves the resource management problem for an operator of an ultra-dense network with exclusive access to a pool of frequency resources, while the second scenario applies to the management of the network density of collocated UDNs that belong to multiple operators sharing the same frequency spectrum. Simulation results demonstrate how effectively the algorithms can adapt the allocation of the spectrum allocation and the density of active access nodes over space and time.

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Lemieux, Vincent, Dany Garant, Denis Reale, and Patrick Bergeron. "Spatio-temporal variation in oxidative status regulation in a small mammal." PeerJ 7 (October 8, 2019): e7801. http://dx.doi.org/10.7717/peerj.7801.

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Life-history allocation trade-offs are dynamic over time and space according to the ecological and demographical context. Fluctuations in food availability can affect physiological trade-offs like oxidative status regulation, reflecting the balance between pro-oxidant production and antioxidant capacity. Monitoring the spatio-temporal stability of oxidative status in natural settings may help understanding its importance in ecological and evolutionary processes. However, few studies have yet conducted such procedures in wild populations. Here, we monitored individual oxidative status in a wild eastern chipmunk (Tamias striatus) population across the 2017 summer active period and over three study sites. Oxidative damage (MDA: Malondialdehyde levels) and non-enzymatic antioxidant levels (FRAP: Ferric reducing antioxidant power and HASC: Hypochlorous acid shock capacity) were quantified across time and space using assays optimized for small blood volumes. Our results showed an increase in oxidative damage mirrored by a decrease in FRAP throughout the season. We also found different antioxidant levels among our three study sites for both markers. Our results also revealed the effects of sex and body mass on oxidative status. Early in the active season, females and individuals with a greater body mass had higher oxidative damage. Males had higher HASC levels than females throughout the summer. This study shows that oxidative status regulation is a dynamic process that requires a detailed spatial and temporal monitoring to yield a complete picture of possible trade-offs between pro-oxidant production and antioxidant capacity.

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Vasermanis, Edgars K., Nicholas A. Nechval, Konstantin N. Nechval, and Kristine N. Rozite. "OPTIMAL AIRLINE SEAT INVENTORY CONTROL FOR MULTI‐LEG FLIGHTS." Aviation 8, no. 4 (December 31, 2004): 10–15. http://dx.doi.org/10.3846/16487788.2004.9635883.

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Airline seat inventory control is about “selling the right seats to the right people at the right time”. In this paper, the problem of determining optimal booking policy for multiple fare classes in a pool of identical seats for multi‐leg flights is considered. During the time prior to departure of a multi‐leg flight, decisions must be made concerning the allocation of reserved seats to passengers requesting space on the full or partial spans of the flight. It will be noted that in the case of multi‐leg flights the long‐haul passengers are often unable to obtain seats because the shorter‐haul passengers block them. For large commercial airlines, efficiently setting and updating seat allocation targets for each passenger category on each multi‐leg flight is an extremely difficult problem. This paper presents static and dynamic models of airline seat inventory control for multi‐leg flights with multiple fare classes, which allow one to maximize the expected contribution to profit. The dynamic model uses the most recent demand and capacity information and allows one to allocate seats dynamically and anticipatorily over time.

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Derakhshan-Barjoei, Pouya, Gholamreza Dadashzadeh, Farbod Razzazi, and S. Mohammad Razavizadeh. "Power and Time Slot Allocation in Cognitive Relay Networks Using Particle Swarm Optimization." Scientific World Journal 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/424162.

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The two main problems in cognitive radio networks are power and time slot allocation problems which require a precise analysis and guarantee the quality of service in both the primary and secondary users. In this paper, these two problems are considered and a method is proposed to solve the resulting optimization problem. Our proposed method provides an improved performance in solving the constrained nonlinear multiobject optimization for the power control and beamforming in order to reach the maximum capacity and proper adaption of time slots, and as a result a new scheme for joint power and time slot allocation in cognitive relay networks is proposed. We adopt space diversity access as the secondary users access scheme and divide the time between multiple secondary users according to their contribution to primary user’s transmission. Helping primary users provides more opportunities for secondary users to access the channel since the primary users can release the channel sooner. In contrast, primary network leases portion of channel access time to the secondary users for their transmission using particle swarm optimization (PSO). Numerical studies show good performance of the proposed scheme with a dynamic cost function in a nonstationary environment.

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Journal articles on the topic 'Spare Capacity Allocation'

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