Search results for: weighted scheduling

Authors: Reham A. El-mayet, Hesham M. El-Badawy, Salwa H. Elramly

Abstract:

New generation mobile communication networks have the ability of supporting triple play. In order that, Orthogonal Frequency Division Multiplexing (OFDM) access techniques have been chosen to enlarge the system ability for high data rates networks. Many of cross-layer modeling and optimization schemes for Quality of Service (QoS) and capacity of downlink multiuser OFDM system were proposed. In this paper, the Maximum Weighted Capacity (MWC) based resource allocation at the Physical (PHY) layer is used. This resource allocation scheme provides a much better QoS than the previous resource allocation schemes, while maintaining the highest or nearly highest capacity and costing similar complexity. In addition, the Delay Satisfaction (DS) scheduling at the Medium Access Control (MAC) layer, which allows more than one connection to be served in each slot is used. This scheduling technique is more efficient than conventional scheduling to investigate both of the number of users as well as the number of subcarriers against system capacity. The system will be optimized for different operational environments: the outdoor deployment scenarios as well as the indoor deployment scenarios are investigated and also for different channel models. In addition, effective capacity approach [1] is used not only for providing QoS for different mobile users, but also to increase the total wireless network's throughput.

Keywords: Cross-layer, effective capacity, LTE, OFDM, QoS, resource allocation, wireless networks.

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Authors: Dongliang Wang, Jun Han, Dianfu Ma, Xianqi Zhao

Abstract:

Avionics software is safe-critical embedded software and its architecture is evolving from traditional federated architectures to Integrated Modular Avionics (IMA) to improve resource usability. ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Arinc653 uses two-level scheduling strategies, but current modeling tools only apply to simple problems of Arinc653 two-level scheduling, which only contain time property. In avionics industry, we are always manually allocating tasks and calculating the timing table of a real-time system to ensure it-s running as we design. In this paper we represent an automatically generating strategy which applies to the two scheduling problems with dependent constraints in Arinc653 partition run-time environment. It provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or not

Keywords: Arinc653, scheduling, task allocation, simulation.

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Authors: Vishnu Kant Soni, Raksha Sharma, Manoj Kumar Mishra

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Grid computing is a high performance computing environment to solve larger scale computational applications. Grid computing contains resource management, job scheduling, security problems, information management and so on. Job scheduling is a fundamental and important issue in achieving high performance in grid computing systems. However, it is a big challenge to design an efficient scheduler and its implementation. In Grid Computing, there is a need of further improvement in Job Scheduling algorithm to schedule the light-weight or small jobs into a coarse-grained or group of jobs, which will reduce the communication time, processing time and enhance resource utilization. This Grouping strategy considers the processing power, memory-size and bandwidth requirements of each job to realize the real grid system. The experimental results demonstrate that the proposed scheduling algorithm efficiently reduces the processing time of jobs in comparison to others.

Keywords: Grid computing, Job grouping and Jobscheduling.

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Authors: S.Aranganayagi, K.Thangavel

Abstract:

K-Modes is an extension of K-Means clustering algorithm, developed to cluster the categorical data, where the mean is replaced by the mode. The similarity measure proposed by Huang is the simple matching or mismatching measure. Weight of attribute values contribute much in clustering; thus in this paper we propose a new weighted dissimilarity measure for K-Modes, based on the ratio of frequency of attribute values in the cluster and in the data set. The new weighted measure is experimented with the data sets obtained from the UCI data repository. The results are compared with K-Modes and K-representative, which show that the new measure generates clusters with high purity.

Keywords: Clustering, categorical data, K-Modes, weighted dissimilarity measure

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Authors: T. Vigneswari, M. A. Maluk Mohamed

Abstract:

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques.

Keywords: Grid Computing, Grid Scheduling, Heterogeneous Earliest Finish Time (HEFT), Artificial Bee colony (ABC) Algorithm, Resource Management.

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Authors: Marcel Rojahn, Edzard Weber, Norbert Gronau

Abstract:

Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in)consistence for the research field of job-shop scheduling by a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability and combinability of scheduling methods is unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods.

Keywords: Job-shop scheduling, JSP, terminology, notation, standardization.

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

Abstract:

Concurrent planning of project scheduling and material ordering can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance.

Keywords: Material ordering, project scheduling, quantity discount, space availability.

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Authors: Joselito Medina Marin, Norberto Hernández Romero, Juan Carlos Seck Tuoh Mora, Erick S. Martinez Gomez

Abstract:

The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.

Keywords: Flow-shop scheduling problem, makespan, Petri nets, state equation.

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Authors: Chia-Hung Chen, Shangyao Yan

Abstract:

The solution algorithm, based on Lagrangian relaxation, a sub-gradient method and a heuristic to find the upper bound of the solution, is proposed to solve the coordinated fleet routing and flight scheduling problems. Numerical tests are performed to evaluate the proposed algorithm using real operating data from two Taiwan airlines. The test results indicate that the solution algorithm is a significant improvement over those obtained with CPLEX, consequently they could be useful for allied airlines to solve coordinated fleet routing and flight scheduling problems.

Keywords: Coordinated flight scheduling, multiple commodity network flow problem, Lagrangian relaxation.

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Authors: Mohammad Mirabi

Abstract:

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Keywords: Hybrid genetic algorithm, Scheduling, Permutationflow-shop, Sequence dependent

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Authors: A. Shirzadeh Chaleshtari, Sh. Shadrokh

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Renewable and non-renewable resource constraints have been vast studied in theoretical fields of project scheduling problems. However, although cumulative resources are widespread in practical cases, the literature on project scheduling problems subject to these resources is scant. So in order to study this type of resources more, in this paper we use the framework of a resource constrained project scheduling problem (RCPSP) with finish-start precedence relations between activities and subject to the cumulative resources in addition to the renewable resources. We develop a branch and bound algorithm for this problem customizing precedence tree algorithm of RCPSP. We perform extensive experimental analysis on the algorithm to check its effectiveness and performance for solving different instances of the problem in question.

Keywords: Resource constrained project scheduling problem, cumulative resources, branch and bound algorithm, precedence tree.

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Authors: Sayeed Salam

Abstract:

This paper presents an efficient emission constrained hydrothermal scheduling algorithm that deals with nonlinear functions such as the water discharge characteristics, thermal cost, and transmission loss. It is then incorporated into the hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.

Keywords: Emission constraint, Hydrothermal coordination, and Hydrothermal scheduling algorithm.

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Authors: Petra Heribanová, Jaroslav Polec, Michal Martinovič

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In this paper we propose a new content-weighted method for full reference (FR) video quality control using a region of interest (ROI) and wherein two-component weighted metrics for Deaf People Video Communication. In our approach, an image is partitioned into region of interest and into region "dry-as-dust", then region of interest is partitioned into two parts: edges and background (smooth regions), while the another methods (metrics) combined and weighted three or more parts as edges, edges errors, texture, smooth regions, blur, block distance etc. as we proposed. Using another idea that different image regions from deaf people video communication have different perceptual significance relative to quality. Intensity edges certainly contain considerable image information and are perceptually significant.

Keywords: Video quality assessment, weighted MSE.

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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Authors: Jain-Shing Liu

Abstract:

In this work, we study the problem of determining the minimum scheduling length that can satisfy end-to-end (ETE) traffic demand in scheduling-based multihop WSNs with cooperative multiple-input multiple-output (MIMO) transmission scheme. Specifically, we present a cross-layer formulation for the joint routing, scheduling and stream control problem by incorporating various power and rate adaptation schemes, and taking into account an antenna beam pattern model and the signal-to-interference-and-noise (SINR) constraint at the receiver. In the context, we also propose column generation (CG) solutions to get rid of the complexity requiring the enumeration of all possible sets of scheduling links.

Keywords: Wireless Sensor Networks, Cross-Layer Design, CooperativeMIMO System, Column Generation.

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Authors: K. -H. Yang

Abstract:

In the past, the quay crane operations have been well studied. There were a certain number of scheduling algorithms for quay crane operations, but without considering some nuisance factors that might disrupt the quay crane operations. For example, bad grapples make a crane unable to load or unload containers or a sudden strong breeze stops operations temporarily. Although these disruptive conditions randomly occur, they influence the efficiency of quay crane operations. The disruption is not considered in the operational procedures nor is evaluated in advance for its impacts. This study applies simulation and optimization approaches to develop structures of pre-analysis and post-analysis for the Quay Crane Scheduling Problem to deal with disruptive scenarios for quay crane operation. Numerical experiments are used for demonstrations for the validity of the developed approaches.

Keywords: Disruptive Quay Crane Scheduling, pre-analysis, post-analysis, disruption.

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Authors: Ahmad Rabanimotlagh

Abstract:

In this paper an ant colony optimization algorithm is developed to solve the permutation flow shop scheduling problem. In the permutation flow shop scheduling problem which has been vastly studied in the literature, there are a set of m machines and a set of n jobs. All the jobs are processed on all the machines and the sequence of jobs being processed is the same on all the machines. Here this problem is optimized considering two criteria, makespan and total flow time. Then the results are compared with the ones obtained by previously developed algorithms. Finally it is visible that our proposed approach performs best among all other algorithms in the literature.

Keywords: Scheduling, Flow shop, Ant colony optimization, Makespan, Flow time

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Authors: C. E. Nugraheni, L. Abednego

Abstract:

This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as metaheuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: Hyper-heuristics, evolutionary algorithms, production scheduling.

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Authors: S. Balaji, V. Swaminathan, K. Kannan

Abstract:

The Maximum Weighted Independent Set (MWIS) problem is a classic graph optimization NP-hard problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the MWIS problem is to find a vertex set S V whose total weight is maximum subject to no two vertices in S are adjacent. This paper presents a novel approach to approximate the MWIS of a graph using minimum weighted vertex cover of the graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the proposed algorithm can yield better solutions than other existing algorithms found in the literature for solving the MWIS.

Keywords: weighted independent set, vertex cover, vertex support, heuristic, NP - hard problem.

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Authors: B. Arun Kumar, T. Ravichandran

Abstract:

Workflow scheduling is an important part of cloud computing and based on different criteria it decides cost, execution time, and performances. A cloud workflow system is a platform service facilitating automation of distributed applications based on new cloud infrastructure. An aspect which differentiates cloud workflow system from others is market-oriented business model, an innovation which challenges conventional workflow scheduling strategies. Time and Cost optimization algorithm for scheduling Hybrid Clouds (TCHC) algorithm decides which resource should be chartered from public providers is combined with a new De-De algorithm considering that every instance of single and multiple workflows work without deadlocks. To offset this, two new concepts - De-De Dodging Algorithm and Priority Based Decisive Algorithm - combine with conventional deadlock avoidance issues by proposing one algorithm that maximizes active (not just allocated) resource use and reduces Makespan.

Keywords: Workflow Scheduling, cloud workflow, TCHC algorithm, De-De Dodging Algorithm, Priority Based Decisive Algorithm (PBD), Makespan.

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Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

Abstract:

As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focusses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: Auto-ID, Construction Logistic, Fuzzy, Monitoring, RFID, Scheduling.

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Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

Abstract:

This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: Flexible job shop scheduling, Decision tree, Priority rules, Case study.

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Authors: Ali Abdi Kordani, Hamid Bigdelirad, Sid Mohammad Boroomandrad

Abstract:

Operating Urban Bus Transit System is a phenomenon that has a major role in transporting passengers in cities. There are many factors involved in planning and operating an Urban Bus Transit System, one of which is selecting optimized number of stops and scheduling of bus fleet departure. In this paper, we tried to introduce desirable methodology to select number of stops and schedule properly. Selecting the right number of stops causes convenience in accessibility and reduction in travel time and finally increase in public preference of this transportation mode. The achieved results revealed that number of stops must reduce from 33 to 25. Also according to scheduling and conducted economic analysis, the number of buses must decrease from 17 to 11 to have the most appropriate status for the Bus Organization.

Keywords: Number of optimized stops, organizing bus system, scheduling, urban transit.

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Authors: M. Haddadzade, M. R. Razfar, M. Farahnakian

Abstract:

Integration of process planning and scheduling functions is necessary to achieve superior overall system performance. This paper proposes a methodology for integration of process planning and scheduling for prismatic component that can be implemented in a company with existing departments. The developed model considers technological constraints whereas available time for machining in shop floor is the limiting factor to produce multiple process plan (MPP). It takes advantage of MPP while guarantied the fulfillment of the due dates via using overtime. This study has been proposed to determinate machining parameters, tools, machine and amount of over time within the minimum cost objective while overtime is considered for this. At last the illustration shows that the system performance is improved by as measured by cost and compatible with due date.

Keywords: Due date, Integration, Multiple process plan, Process planning, Scheduling.

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Authors: Phruksaphanrat B.

Abstract:

This research proposes a preemptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of makespan. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, preemptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. 

Keywords: Multi-mode resource constrained project scheduling problem, Fuzzy set, Goal programming, Preemptive fuzzy goal programming.

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Authors: Dr. L. Arockiam, A. Aloysius

Abstract:

In general, class complexity is measured based on any one of these factors such as Line of Codes (LOC), Functional points (FP), Number of Methods (NOM), Number of Attributes (NOA) and so on. There are several new techniques, methods and metrics with the different factors that are to be developed by the researchers for calculating the complexity of the class in Object Oriented (OO) software. Earlier, Arockiam et.al has proposed a new complexity measure namely Extended Weighted Class Complexity (EWCC) which is an extension of Weighted Class Complexity which is proposed by Mishra et.al. EWCC is the sum of cognitive weights of attributes and methods of the class and that of the classes derived. In EWCC, a cognitive weight of each attribute is considered to be 1. The main problem in EWCC metric is that, every attribute holds the same value but in general, cognitive load in understanding the different types of attributes cannot be the same. So here, we are proposing a new metric namely Attribute Weighted Class Complexity (AWCC). In AWCC, the cognitive weights have to be assigned for the attributes which are derived from the effort needed to understand their data types. The proposed metric has been proved to be a better measure of complexity of class with attributes through the case studies and experiments

Keywords: Software Complexity, Attribute Weighted Class Complexity, Weighted Class Complexity, Data Type

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Authors: Lu Yanhui, Wang Chunming, Yin Changchuan, Yue Guangxin

Abstract:

In this paper, we address the problem of adaptive radio resource allocation (RRA) and packet scheduling in the downlink of a cellular OFDMA system, and propose a downlink multi-carrier proportional fair (MPF) scheduler and its joint with adaptive RRA algorithm to distribute radio resources among multiple users according to their individual QoS requirements. The allocation and scheduling objective is to maximize the total throughput, while at the same time maintaining the fairness among users. The simulation results demonstrate that the methods presented provide for user more explicit fairness relative to RRA algorithm, but the joint scheme achieves the higher sum-rate capacity with flexible parameters setting compared with MPF scheduler.

Keywords: OFDMA, adaptive radio resource allocation, scheduling, QoS.

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

Abstract:

This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: Time Utility Function/ Utility Accrual (TUF/UA) scheduling, Real-time system (RTS), Backward Recovery, Multiprocessor, Discrete Event Simulation (DES).

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

Abstract:

Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is then important in a first step to optimize household consumptions to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipments starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So the ceiling would no longer be fixed. The scheduling would be done on two scales, on the one hand per dwelling, and secondly, at the level of a residential complex.

Keywords: Smart grid, Energy box, Scheduling, Gang Model, Energy consumption, Energy management system, and Wireless Sensor Network.

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Authors: José M. Merigó, Anna M. Gil-Lafuente

Abstract:

We study different types of aggregation operators such as the ordered weighted averaging (OWA) operator and the generalized OWA (GOWA) operator. We analyze the use of OWA operators in the Minkowski distance. We will call these new distance aggregation operator the Minkowski ordered weighted averaging distance (MOWAD) operator. We give a general overview of this type of generalization and study some of their main properties. We also analyze a wide range of particular cases found in this generalization such as the ordered weighted averaging distance (OWAD) operator, the Euclidean ordered weighted averaging distance (EOWAD) operator, the normalized Minkowski distance, etc. Finally, we give an illustrative example of the new approach where we can see the different results obtained by using different aggregation operators.

Keywords: Aggregation operators, Minkowski distance, OWA operators, Selection of strategies.

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