Optimal resource allocation with minimum activation levels and fixed costs

Basso, Antonella; Peccati, Lorenzo

doi:10.1016/s0377-2217(00)00093-x

Cited by 38 publications

(19 citation statements)

References 3 publications

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“…The related work presented here is divided into three parts including: broader survey on resource allocation and telecommunication networking [10][11][12][13][14], previous studies on resource allocation and power control in femtocells [15][16][17][18][19] and the decentralized approaches within the context of femtocells [20,21].…”

Section: Related Workmentioning

confidence: 99%

“…Resource allocation has also been widely investigated in management sciences, where financial and timing constraints are more critical. For example, the authors in [11] analyze the resource allocation problem for the running projects, by taking into account both the minimum and maximum activation levels and fixed costs, where some projects are in maximum activation levels while others are in minimum level. Authors exploited dynamic programming approach for finding the optimum solution.…”

Section: Related Workmentioning

confidence: 99%

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A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks

Shahid

Aslam

Lee

2013

Entropy

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Femtocells represent a novel configuration for existing cellular communication, contributing towards the improvement of coverage and throughput. The dense deployment of these femtocells causes significant femto-macro and femto-femto interference, consequently deteriorating the throughput of femtocells. In this study, we compare two heuristic approaches, i.e., particle swarm optimization (PSO) and genetic algorithm (GA), for joint power assignment and resource allocation, within the context of the femtocell environment. The supposition made in this joint optimization is that the discrete power levels are available for the assignment. Furthermore, we have employed two variants of each PSO and GA: inertia weight and constriction factor model for PSO, and twopoint and uniform crossover for GA. The two proposed algorithms are in a decentralized manner, with no involvement of any centralized entity. The comparison is carried out between the two proposed algorithms for the aforementioned joint optimization problem. The contrast includes the performance metrics: including average objective function, min-max throughput of the femtocells, average throughput of the femto users, outage rate and time complexity. The results demonstrate that the decentralized PSO constriction factor outperforms the others in terms of the aforementioned performance metrics.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks

Shahid

Aslam

Lee

2013

Entropy

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“…The domain is thus the list of the section classes corresponding to the student as defined in Eq. (10). The constraints of this model are the capacity of the classes; the number of students in a class cannot exceed its capacity, Eq.…”

Section: The Csop Modelmentioning

confidence: 99%

“…Dynamic programming has been used to optimise a portfolio in a project financing firm [10]. Neighbourhood search [11], particle swarm optimisation [12] and genetic algorithms [13] have been applied to the classical problem of assigning workers to jobs where the objectives are to maximize the efficiency and to minimize the cost.…”

Section: Introductionmentioning

confidence: 99%

A Constraint-Based Approach for Classes Setting-Up Problems in Secondary Schools

Nogareda¹,

Camacho²

2017

Int. j. simul. model.

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In this paper, we present the problem of allocating students to classes in Swiss secondary schools, where students have different profiles due to their level in some fields or to the options they attend. The pedagogical objective is to have a high diversity of profiles within a class and similarity between classes. In order to achieve this goal, the problem is modelled as a resource allocation problem (RAP), where students are resources, using a constraint satisfaction optimisation approach (CSOP). The RAP is then solved in two different ways, with a solver for CSOP, and with an ant colony optimisation algorithm (ACO). Eight real datasets are used to compare their performance. The ACO algorithm provides better solutions than the CSOP solver in a shorter time. Results show that the pheromones used in the ACO help to find better solutions in a much smaller amount of time. The short computation time enables the school's directors to simulate different compositions of their future classes before having the final results of the last exams.

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“…An efficiency based measure to enable a comparison to be made between alternative sets of MRLs is also presented. (Basso and Peccati [5]) introduced a dynamic programming algorithm to get optimal resource allocation with both minimum and maximum activation levels and fixed costs. Yan et al [36] discussed a typical inverse optimization problem on the generalized DEA model to identify how to control or adjust the changes in the input and output such that the efficiency index of DMUs concerned is preserved.…”

Section: Introductionmentioning

confidence: 99%

A Data Envelopment Analysis Based Approach for Target Setting and Resource Allocation: Application in Gas Companies

Mottaghi¹,

Ebrahimnejad²,

Ezzati³

et al. 2015

HJMS

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Resource allocation is an important application of data envelopment analysis and has been investigated by many researchers and managers from both economic and managerial field. In real managerial and economical decisions, situations often occur when extra productions of goods are utilized and the decision maker (DM) would like to determine the numbers of extra products that each unit can produced. In this paper, several methods based on the data envelopment analysis for resource allocation in such situations are introduced that can help the managers to make better decisions. The primary aim of this paper is to allocate resources such that the inefficient decision making units (DMUs) to become efficient as possible. For this aim, firstly several homogeneous units under the control of a central unit are considered and then the efficiency of each unit is determined. In addition, if the production of additional products seems logical, the DM wants to know how much of additional outputs should be produced by each unit such that the total outputs reach to a predetermined level. In this case the proposed algorithms determine quantities of the consumed input and produced output levels for each DMU to obtain the desirable output level. For using the whole power of system, the multi objective programming (MOP) problem has been used. A numerical example is given to show the solution process to improve the clarity of the proposed method. Finally, the real data of a gas company extracted from extant literature are used to demonstrate the proposed method.

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Optimal resource allocation with minimum activation levels and fixed costs

Cited by 38 publications

References 3 publications

A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks

A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks

A Constraint-Based Approach for Classes Setting-Up Problems in Secondary Schools

A Data Envelopment Analysis Based Approach for Target Setting and Resource Allocation: Application in Gas Companies

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