# José E. Gallardo's research while affiliated with University of Malaga and other places

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## Publications (26)

We consider an operational model of suicide bombing attacks—an increasingly prevalent form of terrorism—against specific targets, and the use of protective countermeasures based on the deployment of detectors over the area under threat. These detectors have to be carefully located in order to minimize the expected number of casualties or the econom...

Each instance contains n strings (possibly of different lengths) defined over an alphabet of m symbols. Some instances have been randomly generated and some other instances have been obtained from biological sequences.

Suicide bombing is an infamous form of terrorism that is becoming increasingly prevalent in the current era of global terror warfare. We consider the case of targeted attacks of this kind, and the use of detectors distributed over the area under threat as a protective countermeasure. Such detectors are non-fully reliable, and must be strategically...

Memetic algorithms (MAs) constitute a search and optimization paradigm based on the orchestrated interplay between global and local search components, and have the exploitation of specific problem knowledge as one of their central tenets. MAs can take different forms although a classical incarnation involves the integration of independent search pr...

The Far From Most String Problem (FFMSP) is a string selection problem. The objective is to find a string whose distance to other strings in a certain input set is above a given threshold for as many of those strings as possible. This problem has links with some tasks in computational biology and its resolution has been shown to be very hard. We pr...

The shortest common supersequence problem is a classical problem with many applications in different fields such as planning, Artificial Intelligence and especially in Bioinformatics. Due to its NP-hardness, we can not expect to efficiently solve this problem using conventional exact techniques. This paper presents a heuristic to tackle this proble...

As mentioned in previous chapters in this volume, metaheuristics (and specifically MAs) have a part of their raison d’etre in practically solving problems whose resolution would be otherwise infeasible by means of other non-heuristic approaches. Such alternative non-heuristic approaches are complete methods that –unlike heuristics– do guarantee tha...

This paper deals with the construction of binary sequences with low autocorrelation, a very hard problem with many practical applications. The paper analyzes several metaheuristic approaches to tackle this kind of sequences. More specifically, the paper provides an analysis of different local search strategies, used as standalone techniques and emb...

A weighted constraint satisfaction problem (WCSP) is a constraint satisfaction problem in which preferences among solutions can be expressed. Bucket elimination is a complete technique commonly used to solve this kind of constraint satisfaction problem. When the memory required to apply bucket elimination is too high, a heuristic method based on it...

The maximum density still life problem (MDSLP) is a hard constraint optimization problem based on Conway's game of life. It is a prime example of weighted constrained optimization problem that has been recently tackled in the constraint-programming community. Bucket elimination (BE) is a complete technique commonly used to solve this kind of constr...

An important branch of hybrid metaheuristics concerns the hybridization with branch & bound derivatives. In this chapter we
present examples for two different types of hybridization. The first one concerns the use of branch & bound features within
construction-based metaheuristics in order to increase their efficiancy. The second example deals with...

This book constitutes the refereed proceedings of the 5th International Workshop on Hybrid Metaheuristics, HM 2008, held in Malaga, Spain, in October 2008.
The 14 revised full papers presented were carefully reviewed and selected from 33 submissions. The papers discuss specific aspects of combinations of metaheuristics and other solving techniques...

A phylogenetic tree represents the evolutionary history for a collection of organisms. We consider the problem of inferring such a tree given a certain set of data (genomic, proteomic, or even morphological). Given the computational hardness of this problem, exact approaches are inherently limited. However, exact techniques can still be useful to e...

The Shortest Common Supersequence Problem (SCSP) is a well-known hard combinatorial optimization problem that formalizes many real world problems. This paper presents a novel randomized search strategy, called probabilistic beam search (PBS), based on the hybridiza- tion between beam search and greedy constructive heuristics. PBS is competitive (an...

Branch-and-bound (BnB) and memetic algorithms represent two very different approaches for tackling combinatorial optimization problems. However, these approaches are compatible. In this correspondence, a hybrid model that combines these two techniques is considered. To be precise, it is based on the interleaved execution of both approaches. Since t...

Finding binary sequences with low autocorrelation is a very hard problem with many practical applications. In this paper we analyze several metaheuristic approaches to tackle the construction of this kind of sequences. We focus on two different local search strategies, steepest descent local search (SDLS) and tabu search (TS), and their use both as...

Bucket elimination (BE) is an exact technique based on vari- able elimination, commonly used for solving constraint satisfaction prob- lems. We consider the hybridization of BE with evolutionary algorithms endowed with tabu search. The resulting memetic algorithm (MA) uses BE as a mechanism for recombining solutions, providing the best possible chi...

Bucket elimination (BE) is an exact technique based on vari- able elimination. It has been recently used with encouraging results as a mechanism for recombining solutions in a memetic algorithm (MA) for the still life problem, a hard constraint optimization problem based on Conway's game of life. This paper studies expanded multi-level mod- els in...

A hybridization of an evolutionary algorithm (EA) with the branch and bound method (B&B) is presented in this paper. Both tech- niques cooperate by exchanging information, namely lower bounds in the case of the EA, and partial promising solutions in the case of the B&B. The multidimensional knapsack problem has been chosen as a bench- mark. To be p...

Branch-and-bound and evolutionary algorithms represent two very different approaches for tackling combinatorial optimization problems. These approaches are not incompatible though. In this paper, we consider a hybrid model that combines these two techniques. To be precise, it is based on the interleaved execution of both approaches, and has a heuri...

## Citations

... The primary novelty of this work, from the theoretical point of view, is the utilization of body posture data for the task at hand. There have been past works, like (Cotta and Gallardo, 2019), (Ahmad et al., 2019), and (Singer and Golan, 2019) that also address the task of identifying a suicide bomber, however, there contribution is either limited to the placement of sensors (Cotta and Gallardo, 2019), analysis of textual data for inclination towards the act of executing a suicidal attack (Ahmad et al., 2019) or performing post attack analysis using the available data (Singer and Golan, 2019). To the best of our knowledge, there is no work available that identifies a suicide bomber in a real-world environment during the window when the attack is being executed. ...

... The approach is able to identify the subjects with metallic peripherals and dielectric components. Cotta and Gallardo (2018) propose a suicide bomber detectors' placement technique in a threat area with known targets using different algorithms. The aim is to maximize the detection chances of suicide bombers when they enter in a specific area. ...

... Memetic algorithms are a type of hybrid-optimisation methods which, in its classical version, consists in executing a local search inside the execution of an external genetic algorithm (GA) (Cotta et al. 2016;Neri et al. 2012). The general scheme of this MA is depicted below in Algorithm 1. ...

... It is possible to define a more intensive recombination approach by taking ideas from complete techniques [59]. More precisely, a complete technique can be used to explore the set of potential solutions that can be created using a given collection of parents, returning the best solution attainable. ...

Reference: Memetic algorithms

... A memetic algorithm that uses the greedy randomized adaptive search procedure (GRASP) metaheuristic and path relinking to initialise and mutate the population was proposed [53]. However, the scalability of the MA was untested. ...

... In order to maximize the code reuse and to favor testing of Hybrid Metaheuristics (Blum and Roli, 2008), all heuristic methods should be implemented using the Heuristic class abstraction. With this abstraction we have already been able to implement the following methods: First Improvement, Best Improvement, Hill Climbing and other classical heuristic strategies (Hansen and Mladenovi´cMladenovi´c, 2006); Iterated Local Search, Simulated Annealing, Tabu Search, Variable Neighborhood Search and other basic versions of many famous trajectory based metaheuristics (Glover and Kochenberger, 2003); and, finally, the basic versions of population based metaheuristics Genetic Algorithm and Memetic Algorithm ( Glover and Kochenberger, 2003). ...

... Biology [88,89,185,186,196,200,237,236,238,239,267,268] Chemistry [77,79,78,76,107,193] Chemical Engineering [47,74,138,139,148,156,240,254,255,251,253,252] Data Compression [273,167,269,278,244,144] Drug Design [103,190,191,250,249,128,159, 108] Electronic Engineering [133,270,100,204,41,96,199,206,46,97,117,205,113,116,112,209,115,213,114] more exotic Memetic Algorithms that use heuristics of only one type, or multiple heuristics of each type exist. The adaptability of Memetic Algorithms to parallel implementation also encourages the use of multiple different types of heuristics simultaneously -the exploitation of all available knowledge is, after all, the central idea of the Memetic paradigm. ...

Reference: Memetic algorithms

... If m knapsacks exist, the problem becomes the MKP in which each knapsack has a different upper weight limit b i , and an item j has a different weight a ij for each knapsack i. The objective is to find a set of items with maximal profit such that the capacity of each knapsack is not exceeded [36]. The MKP can be formulated as follows: ...

... Finally, a greedy operator (CS) was designed to search a consensus tree among the parents. It applies the NNI operator on the T 1 parent until the offspring reaches a random determined distance r (Robinson-Foulds distance [53]) from both parents (in Figure 3, we show a scheme of the four crossover operators inspired on the work of [54]). Finally, a uniform crossover operator combines the parameters of the evolutionary model employed in the likelihood calculation for each parent. ...

... Therefore, the goal of genome projects is to reconstruct the original genome sequence of an organism. To achieve the goal, DNA fragment assembly process is divided into three phases [7], [8]: ...