Showing papers in "International Journal of Computational Intelligence Systems in 2015"
TL;DR: This paper surveys the latest status of fuzzy multicriteria decision-making methods and classify these methods dividing into two parts: fuzzy multiattribute decision- Making (MADM) and fuzzy multiobjective decision- making (MODM).
Abstract: Multicriteria decision-making (MCDM) refers to making decisions in the presence of multiple and usually conflicting criteria. Fuzzy decision-making is used where vague and incomplete data exist for the solution. Fuzzy multicriteria decision-making is one of the most popular problems handled by the researchers in the literature. In this paper, we survey the latest status of fuzzy multicriteria decision-making methods and classify these methods dividing into two parts: fuzzy multiattribute decision-making (MADM) and fuzzy multiobjective decision-making (MODM). Most of the publications are on fuzzy MADM since there are a plenty of classical multiattribute decision-making methods in the literature. Tabular and graphical illustrations for each method are given.
376 citations
TL;DR: The linguistic score index and linguistic accuracy index of the LIFN are introduced in order to process the multiple attribute decision making (MADM) with LIFNs, and an approach to handle MADM under LifNs environment is proposed.
Abstract: Motivated by intuitionistic fuzzy sets and fzzy linguistic approach, this article proposes the concept of linguistic intuitionistic fuzzy numbers (LIFNs) where membership and and nonmembership are represented as linguistic terms. In order to process the multiple attribute decision making (MADM) with LIFNs, we introduce the linguistic score index and linguistic accuracy index of the LIFN. Simultaneously, the operation laws for LIFNs are defined and the related properties of the operation laws are studied. Further, some aggregation operators are developed, involving the linguistic intuitionistic fuzzy weighted averaging (LIFWA) operator, linguistic intuitionistic fuzzy ordered weighted averaging (LIFOWA) operator and linguistic intuitionistic fuzzy hybrid averaging (LIFHA) operator, etc., which can be utilized to aggregate preference information taking the form of LIFNs. Based on the LIFWA and the LIFHA operators, we propose an approach to handle MADM under LIFNs environment. Finally, an illustrativ...
188 citations
TL;DR: The classical TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method is extended to solve MCDM problems dealing with HFLTSs and considering the decision maker's psychological behavior.
Abstract: Hesitant fuzzy linguistic term sets (HFLTSs) are very useful for dealing with the situations in which the decision makers hesitate among several linguistic terms to assess an alternative. Some multi-criteria decision-making (MCDM) methods have been developed to deal with HFLTSs. These methods are derived under the assumption that the decision maker is completely rational and do not consider the decision maker's psychological behavior. But some studies about behavioral experiments have shown that the decision maker is bounded rational in decision processes and the behavior of the decision maker plays an important role in decision analysis. In this paper, we extend the classical TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method to solve MCDM problems dealing with HFLTSs and considering the decision maker's psychological behavior. A novel score function to compare HFLTSs more effectively is defined. This function is also used in the proposed TODIM method. Final...
173 citations
TL;DR: Multi-valued neutrosophic sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy- membership and falsity- membership degree to have a set of crisp values between zero and one, respectively.
Abstract: In recent years, hesitant fuzzy sets (HFSs) and neutrosophic sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued neutrosophic sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy- membership and falsity-membership degree have a set of crisp values between zero and one, respectively. Then the operations of multi-valued neutrosophic numbers (MVNNs) based on Einstein operations are defined, and a comparison method for MVNNs is developed depending on the related research of HFSs and Atanassov's intuitionistic fuzzy sets (IFSs). Furthermore, the multi-valued neutrosophic power weighted average (MVNPWA) operator and the multi-valued neutrosophic power weighted geometric (MVNPWG) operator are proposed and the desirable properties of two operators are also discussed. Finally, an approach for solving MCGDM problems is explored by applying the power aggreg...
167 citations
TL;DR: In this paper, a new correlation coefficient measure is presented, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same.
Abstract: This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the proposed weighted correlation coefficient measure of INSs, a decision-making method is developed, which takes into account the influence of the evaluations’ uncertainty and both the objective and subjective weights.
132 citations
TL;DR: This work generalizes hesitant fuzzy linguistic term sets by enabling any non-consecutive linguistic terms in them, and refer to as extended hesitant fuzzy language term sets (EHFLTSs), which are flexible for develop complex decision model.
Abstract: Group decision making problems which organize a group of experts to evaluate a set of alternatives with respect to several criteria are commonly discussed recently. Hesitant fuzzy linguistic term sets, characterized by a set of consecutive linguistic terms, act as a new model for qualitative settings where experts think of several possible linguistic values or richer expressions than a single term. When evaluating an indicator, alternative or variable in group decision making, however, linguistic terms involved in an expression derived by the group may be not always consecutive. Therefore, we generalize hesitant fuzzy linguistic term sets by enabling any non-consecutive linguistic terms in them, and refer to as extended hesitant fuzzy linguistic term sets (EHFLTSs). EHFLTSs can be constructed by the union of hesitant fuzzy linguistic term sets given by individual expert. As owning more desirable mathematical properties, EHFLTSs are flexible for develop complex decision model. Some basic operation ...
131 citations
TL;DR: The Chi-FRBCS-BigData algorithm is proposed, a linguistic fuzzy rule-based classification system that uses the MapReduce framework to learn and fuse rule bases and is able to handle big data classification problems providing competitive results.
Abstract: The big data term is used to describe the exponential data growth that has recently occurred and represents an immense challenge for traditional learning techniques. To deal with big data classification problems we propose the Chi-FRBCS-BigData algorithm, a linguistic fuzzy rule-based classification system that uses the MapReduce framework to learn and fuse rule bases. It has been developed in two versions with different fusion processes. An experimental study is carried out and the results obtained show that the proposal is able to handle these problems providing competitive results.
99 citations
TL;DR: Some properties of the µ–complement of bipolar fuzzy graphs are discussed and a necessary condition for a bipolar fuzzy graph to be self µ-complement is given.
Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. In this paper, we discussed some properties of the µ–complement of bipolar fuzzy graphs. Self µ–complement bipolar fuzzy graphs and self weak µ–complement bipolar fuzzy graphs are defined and a necessary condition for a bipolar fuzzy graph to be self µ–complement is given. We defined busy vertices and free vertices in bipolar fuzzy graphs and studied their image under an isomorphism. Categorical properties of bipolar fuzzy graphs are discussed. Also, we investigated some properties of isomorphism on bipolar fuzzy graphs.
93 citations
TL;DR: The principles and the state-of-the-art of metaheuristic methods for engineering optimization, both the classic and emerging approaches to optimization using metaheuristics are reviewed and analyzed.
Abstract: Metaheuristics has attained increasing interest for solving complex real-world problems. This paper studies the principles and the state-of-the-art of metaheuristic methods for engineering optimization. Both the classic and emerging approaches to optimization using metaheuristics are reviewed and analyzed. All the methods are discussed in three basic types: trajectory-based, in which in each step a new solution is created from the previous one; multi-trajectory-based, in which a multi-start mechanism is used; and population-based, where multiple new solutions are created considering a population of approximate solutions. We further discuss algorithms and strategies to handle multi-modal and multi-objective optimization tasks as well as methods for parallel implementation of metaheuristic algorithms. Then, different software frameworks for metaheuristics are introduced. Finally, several interesting directions are pointed out as future research trends.
77 citations
TL;DR: The conversion methodology of Z – numbers into fuzzy numbers is extended to conversion into standardised generalised fuzzy number so that the methodology is applicable to both positive and negative data values.
Abstract: The new concept of a Z – number has been recently introduced in decision making analysis. This concept is capable of effectively dealing with uncertainty in information about a decision. As this concept is relatively new in fuzzy sets, its underlying theoretical aspects have not been established yet. In this paper, a multi-layer methodology for ranking Z – numbers is proposed for the first time. This methodology consists of two layers: Z – number conversion as the first layer and fuzzy number ranking as the second layer. In this study, the conversion methodology of Z – numbers into fuzzy numbers is extended to conversion into standardised generalised fuzzy number so that the methodology is applicable to both positive and negative data values. The methodology is validated by means of thorough comparison with some established ranking methods for consistency purposes. This methodology is considered as a generic decision making procedure, especially when Z – numbers are applied to real decision making...
65 citations
TL;DR: The problem is solved by using multi-criteria decision making technique with interval Type-2 fuzzy sets and the suggested approach is applied to a real life region and site selection problem of a cement factory.
Abstract: The study proposes a comprehensive and systematic approach for multi-criteria and multi-stage facility location selection problem. To handle with high and more uncertainty in the evaluation and selection processes, the problem is solved by using multi-criteria decision making technique with interval Type-2 fuzzy sets. The study contributes the facility location selection literature by introducing the application of fuzzy TOPSIS method with interval Type-2 fuzzy sets. Finally, the suggested approach is applied to a real life region and site selection problem of a cement factory.
TL;DR: A relatively new decision method called TODIM (an acronym in Portuguese for iterative multi-criteria decision-making -"Tomada de Decisao Iterativa Multicriterio") is improved with fuzziness to prevent the problems of the classical methods.
Abstract: Supplier evaluation and selection is a kind of problem which includes multiple criteria of qualitative and quantitative properties. From different alternatives it requires to find the best option using different criteria and opinions of the decision makers. Because of the judgments or the bias of the decision makers, sometimes classical methods cannot be precise. In this paper, a relatively new decision method called TODIM (an acronym in Portuguese for iterative multi-criteria decision-making -"Tomada de Decisao Iterativa Multicriterio") is improved with fuzziness to prevent the above mentioned problems of the classical methods. A real life case study for a furniture manufacturing company is also be solved.
TL;DR: A new evaluation system for green supplier selection is constructed by considering commercial criterion and environmental criterion, and a decision method with 2-tuple linguistic assessments for green suppliers selection is presented.
Abstract: Under the background of economic globalization, selecting a path of low-carbon economic development and developing green supply chains are the inevitable choice of realizing the sustainable development for the enterprises. In this paper, we investigate the optimization decision problem of supplier selection in green procurement under the mode of low carbon economy. Concretely, we construct a new evaluation system for green supplier selection by considering commercial criterion and environmental criterion, and then present a decision method with 2-tuple linguistic assessments for green supplier selection. In this proposed decision method, all original decision data are transformed into linguistic 2-tuples, and then a ranking method based on 2-tuple weighted averaging (TWA) operator and 2-tuple ordered weighted averaging (TOWA) operator is presented to rank all alternative suppliers. Moreover, we provide an application decision making example of green supplier selection and compare our method with t...
TL;DR: A hybrid MCDM methodology that consists of analytic hierarchy process (AHP) and TOPSIS based on type-2 fuzzy sets is proposed that has been used to determine the most suitable energy storage alternatives.
Abstract: Energy storage alternatives that help storing excess energy and then using it when the system needs it has become more important in recent years Determination of the most suitable energy storage alternative can be analyzed by using multi criteria decision making (MCDM) techniques There are many criteria that affect the best energy storage alternative and the aims are contrasting so, MCDM methodology is a good approach to solve these problems In this paper, a hybrid MCDM methodology that consists of analytic hierarchy process (AHP) and TOPSIS based on type-2 fuzzy sets is proposed To obtain more flexible evaluation and more precise results the proposed methodology combines type-2 fuzzy AHP that used to determine the weights of criteria and type-2 fuzzy TOPSIS methodology that analyzes the alternatives with respect to criteria and weights The proposed methodology has been used to determine the most suitable energy storage alternatives For this aim, 6 electrical energy storage alternatives are
TL;DR: Energy indicators for sustainable development which were introduced by the International Atomic Energy Agency in 2005 were used in this study to determine a renewable energy perspective for Turkey.
Abstract: Energy indicators for sustainable development which were introduced by the International Atomic Energy Agency in 2005 were used in this study to determine a renewable energy perspective for Turkey. The decision making includes social, economic, and environmental factors which affect each other resulting in a multi-criteria decision making problem. The problem is modeled integrating the technique of Analytic Network Process and TOPSIS. Also a sensitivity analysis is performed to monitor the influence of criteria weights on the model results.
TL;DR: The computational results have proved that the proposed hybrid algorithm is an effective approach to solve the multi-objective FJSP.
Abstract: Hybrid sorting immune simulated annealing technique (HSISAT), a Meta - heuristic is proposed for solving the multi objective flexible job-shop scheduling problem (FJSP) The major objectives are distributing the time of machines among the set of operations and scheduling them to minimize the criterion (makespan, total workload and maximum workload) The processing time is sorted for isolating the critical machines and immune simulated annealing (ISA) is applied to increase the convergence speed Several case studies have been taken from the literature to demonstrate the convergence speed of the proposed algorithm The computational results have proved that the proposed hybrid algorithm is an effective approach to solve the multi-objective FJSP
TL;DR: A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced, which includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers.
Abstract: A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. These MCDA methods are described along with a case study on analysis of multicriteria location problem.
TL;DR: A novel discrete wavelet transform (DWT) based color image watermarking method is proposed which embeds the color watermark into host image using uncorrelated color space (UCS) and artificial bee colony (ABC) method and results show that proposed method outperforms other existing methods against the various signal processing attacks.
Abstract: The exponential growth in electronic data over internet have increased the demand of a robust and high quality watermarking method for authentication and copyright protection. In general, the existing digital image watermarking methods embed the binary or gray scale watermark into the host image although most multimedia images are available in color. Moreover, available digital image watermarking methods generally use the correlated color spaces which impose the limitations to researchers for using only one color component at a time for embedding the watermark. Therefore, in this paper, a novel discrete wavelet transform (DWT) based color image watermarking method has been proposed which embeds the color watermark into host image using uncorrelated color space (UCS) and artificial bee colony (ABC) method. The results show that proposed method outperforms other existing methods against the various signal processing attacks.
TL;DR: An effective Weighted Multi-class Least Squares Twin Support Vector Machine approach to address the problem of imbalanced data classification for multi class and employs appropriate weight setting in loss function in order to control the sensitivity of the classifier.
Abstract: The performance of machine learning algorithms is affected by the imbalanced distribution of data among classes. This issue is crucial in various practical problem domains, for example, in medical diagnosis, network intrusion, fraud detection etc. Most efforts so far are mainly focused upon binary class imbalance problem. However, the class imbalance problem is also reported in multi-class scenario. The solutions proposed by the researchers for two-class scenario are not applicable to multi-class domains. So, in this paper, we have developed an effective Weighted Multi-class Least Squares Twin Support Vector Machine (WMLSTSVM) approach to address the problem of imbalanced data classification for multi class. This research work employs appropriate weight setting in loss function, e.g. it adjusts the cost of error for imbalanced data in order to control the sensitivity of the classifier. In order to prove the validity of the proposed approach, the experiment has been performed on fifteen benchmark d...
TL;DR: From the theoretical point of view, algebraic structures of hesitant fuzzy sets are useful for approximate reasoning and decision making to deal with hesitancy of information.
Abstract: In this paper, properties of operations and algebraic structures of hesitant fuzzy sets are investigated. Semilattices of hesitant fuzzy sets with union and intersection are discussed, respectively. By using ⊕ and ⊗ operators, the commutative monoid of hesitant fuzzy sets is provided, moreover, the lattice and distributive lattice of hesitant fuzzy sets are defined on the equivalence class of hesitant fuzzy sets. Based on the distributive lattice of hesitant fuzzy sets, the residuated lattices of hesitant fuzzy sets are constructed by residual implications, which are induced by intersection and ⊗, respectively. From the theoretical point of view, algebraic structures of hesitant fuzzy sets are useful for approximate reasoning and decision making to deal with hesitancy of information.
TL;DR: This paper attempts to develop a method to multi-attribute decision making with Atanassov's interval-valued intuitionistic fuzzy information using prospect theory.
Abstract: Prospect theory is a very effective method to express behavioral decision making under uncertainty. This paper attempts to develop a method to multi-attribute decision making with Atanassov's interval-valued intuitionistic fuzzy information using prospect theory. This method first transforms Atanassov's interval-valued intuitionistic fuzzy variables into the prospect values using the value function in prospect theory. Based on the aspiration levels, Atanassov's intuitionistic fuzzy prospect gain and loss matrices are obtained. Then, using the Atanassov's interval-valued intuitionistic hybrid weight averaging (IVIHWA) operator or the Atanassov's interval-valued intuitionistic hybrid Shapley weight averaging (IVIHSWA) operator, the comprehensive Atanassov's interval-valued intuitionistic fuzzy prospect value of each alternative is calculated. According to the comprehensive Atanassov's interval-valued intuitionistic fuzzy prospect values, a ranking method of alternatives is presented. Finally, two il...
TL;DR: A new intuitionistic fuzzy evidential reasoning (IFER) approach which combines intuitionistic trapezoidal fuzzy numbers and inclusion measure to improve the accuracy of representation and reasoning is proposed.
Abstract: For medical diagnosis, fuzzy Dempster-Shafer theory is extended to model domain knowledge under probabilistic and fuzzy uncertainty. However, there are some information loss using discrete fuzzy sets and traditional matching degree method. This study aims to provide a new evidential structure to reduce information loss. This paper proposes a new intuitionistic fuzzy evidential reasoning (IFER) approach which combines intuitionistic trapezoidal fuzzy numbers and inclusion measure to improve the accuracy of representation and reasoning. The proposed approach has been validated by a stroke diagnosis. It is shown that the IFER approach leads to more accurate results.
TL;DR: It is proved that there exists a one-to-one correspondence between the set of all fuzzy soft sets and theSet of all [0,1]-valued information systems, which illustrates that the authors can research [0-1]-information systems by means of fuzzy soft set.
Abstract: This paper investigates roughness of fuzzy soft sets. A pair of fuzzy soft rough approximations is proposed and their properties are given. Based on fuzzy soft rough approximations, the concept of fuzzy soft rough sets is introduced. New types of fuzzy soft sets such as full, intersection complete and union complete fuzzy soft sets are defined and supported by some illustrative examples. We obtain the structure of fuzzy soft rough sets, investigate the structure of fuzzy topologies induced by fuzzy soft sets, reveal the fact that every finite fuzzy topological space is a fuzzy soft approximation space and discuss fuzzy soft rough relations. We proved that there exists a one-to-one correspondence between the set of all fuzzy soft sets and the set of all [0,1]-valued information systems, which illustrates that we can research [0,1]-information systems by means of fuzzy soft sets.
TL;DR: It is proved the property that the preference over a pair of truth-value vectors is the same for certain predicates in the Compensatory Fuzzy Logic and the Continuous Archimedean Logic.
Abstract: The paper aims to define a new kind of logic, referred to as Archimedean-Compensatory Logic, which is constructed from the unification of two different fuzzy logic systems, namely a continuous Archimedean fuzzy logic and a compensatory fuzzy logic. The paper introduces basic definitions and properties of this new theory. Continuous Archimedean logic is a t-norm and t-conorm logic system and Compensatory Fuzzy Logic can be obtained from quasi-arithmetic mean operators. We will prove the property that the preference over a pair of truth-value vectors is the same for certain predicates in the Compensatory Fuzzy Logic and the Continuous Archimedean Logic.
TL;DR: A Java software with three most efficient classifiers that can be used for IDS is developed and compared it with other options to show the detection accuracy and efficiency of the single and combined classifiers used.
Abstract: In this paper we discuss and analyze some of the intelligent classifiers which allows for automatic detection and classification of networks attacks for any intrusion detection system. We will proceed initially with their analysis using the WEKA software to work with the classifiers on a well-known IDS (Intrusion Detection Systems) dataset like NSL-KDD dataset. The NSL-KDD dataset of network attacks was created in a military network by MIT Lincoln Labs. Then we will discuss and experiment some of the hybrid AI (Artificial Intelligence) classifiers that can be used for IDS, and finally we developed a Java software with three most efficient classifiers and compared it with other options. The outputs would show the detection accuracy and efficiency of the single and combined classifiers used.
TL;DR: A research project for developing and using a ‘Technology Hub’ framework combining Computational Intelligence – Rule-based Reasoning technology and Radio Frequency Identification (RFID) technology in the waste management sector.
Abstract: Protection of the environment is currently a high profile concern and this is resulting in more effective recycling and reuse of materials. This paper outlines a research project for developing and using a ‘Technology Hub’ framework combining Computational Intelligence – Rule-based Reasoning technology and Radio Frequency Identification (RFID) technology in the waste management sector. This framework has been developed using a case study based on a local waste recycling company. The project aims to help recycling companies in tracking, scheduling and intelligently handling incidents of waste movement in order to prevent fly-tipping and improve their management efficiency. Finally, the development procedure for a smart plasterboard waste management system is outlined, which includes a detailed discussion concerning the Rule-based Reasoning system design. This application provides a solution that a company can use to monitor the fleet/waste status and also generate decision support automatically in ...
TL;DR: The aim of this paper is to describe the creation of an integrated traffic simulation system that includes an intelligent traffic lights operating system, dynamic speed limits for speed lanes, lane reservation, road reservation, density regularization or traffic jam avoidance, replanning for blockages and re-routing under slow traffic conditions.
Abstract: It is becoming increasingly likely that in the future most vehicles will be semi-autonomous with communication capabilities and will possess diverse speed capabilities. The aim of this paper is to describe the creation of an integrated traffic simulation system for such settings. While behaviours such as crossing, overtaking, etc. are trivially exhibited, the implemented system includes an intelligent traffic lights operating system, dynamic speed limits for speed lanes, lane reservation, road reservation, density regularization or traffic jam avoidance, replanning for blockages and re-routing under slow traffic conditions.
TL;DR: A novel approach for deriving weights of the decision criteria or alternatives in multi-attribute decision making (MADM) under intuitionistic fuzzy (IF) environment is presented and generates crisp priorities from IF pair-wise comparison matrix.
Abstract: The aim of this paper is to present a novel approach for deriving weights of the decision criteria or alternatives in multi-attribute decision making (MADM) under intuitionistic fuzzy (IF) environment. In order to tackle the uncertainty and imprecision of the practical situations, decision makers’ pair-wise comparison judgments are represented by intuitionistic fuzzy numbers (IFNs). The assessment of the priorities from these IF pair-wise comparison judgments is formulated as an IF decision making problem where goals are described in intuitionistic fuzzy sense. Then by resolving hesitancy via a parameter, IF goals are transformed into fuzzy goals. Finally, aggregation of fuzzy goals and application of the max - min principle lead us to a nonlinear optimization problem whose solution gives the desired crisp priorities. Unlike the other prioritization methods, the proposed approach generates crisp priorities from IF pair-wise comparison matrix. Thus, the proposed approach eliminates the additional r...
TL;DR: The feasibility and effectiveness of the proposed novel approach to decision making based on grey relational analysis and MYCIN certainty factor combination rule and the best alternatives are demonstrated.
Abstract: This paper proposes a novel approach to decision making based on grey relational analysis and MYCIN certainty factor, which describes decision making problems with fuzzy soft sets. Firstly, we utilize grey relational analysis to obtain the grey mean relational degree, and the uncertain degree of various parameters is acquired. On the basis of uncertain degree, we obtain the essence uncertainty factor of each independent alternative with each parameter. Information can be fused in accordance with MYCIN certainty factor combination rule and the best alternatives are achieved. By using three examples, comparing with the mean potentiality approach and giving an application to medical diagnosis problems, the feasibility and effectiveness of the approach are demonstrated.
TL;DR: This work proposes a new algorithm portfolio for this type of problems that incorporates a learning scheme to select, among the metaheuristics that compose it, the most appropriate solver or solvers for each problem, configuration and search stage.
Abstract: Since their first appearance in 1997 in the prestigious journal Science, algorithm portfolios have become a popular approach to solve static problems. Nevertheless and despite that success, they have not received much attention in Dynamic Optimization Problems (DOPs). In this work, we aim at showing these methods as a powerful tool to solve combinatorial DOPs. To this end, we propose a new algorithm portfolio for this type of problems that incorporates a learning scheme to select, among the metaheuristics that compose it, the most appropriate solver or solvers for each problem, configuration and search stage. This method was tested over 5 binary-coded problems (dynamic variants of OneMax, Plateau, RoyalRoad, Deceptive and Knapsack) and compared versus two reference algorithms for these problems (Adaptive Hill Climbing Memetic Algorithm and Self Organized Random Immigrants Genetic Algorithm). The results showed the importance of a good design of the learning scheme, the superiority of the algorithm...