Daniel Riera

Universitat Oberta de Catalunya | UOC · Computer, Multimedia and Telecommunication Studies

Simheuristics combine metaheuristics with simulation in order to solve the optimization problems with stochastic elements. This paper introduces the concept of fuzzy simheuristics, which extends the simheuristics approach by making use of fuzzy techniques, thus allowing us to tackle optimization problems under a more general scenario, which include...

Recent advances in the telecommunication industry offer great opportunities to citizens and organizations in a globally connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as combinatorial optimization problems (COPs). Frequently, these COPs are large-size,...

Learner’s motivation difficulties are recognized as a problem in diverse educational scenarios, reaching up to university degrees. Among other techniques that are often applied by instructors to counteract this issue, those related to the use of gaming elements seem to very promising. In this context, considering the use of game-like properties in...

Telecommunication network-design problems have gained attention over the last decades. Among them, the problem looking for a network design that minimizes total costs, while satisfying users’ demands is well-known. This is the particular case of the Hub Location Problem (HLP). In data communications, a hub is a place of convergence where data arriv...

The concept of vendor managed inventories (VMI) constitutes a promising supply chain management concept. By centralizing inventory management and route planning decisions, overall value chain costs can be reduced. From an optimization perspective, VMI strategies result in the complex inventory routing problem (IRP). This work develops a fast and ef...

Currently, video-games take a prominent place as a medium in society. Thus a generation has grown up playing them and feeling comfortable in a daily life where game-like mechanics have become increasingly prevalent. The result is a breeding ground for tools that use such mechanics to improve learning experiences, such as serious games and gamificat...

This paper proposes a simheuristic algorithm for solving the Arc-Routing Problem with Stochastic Demands. Our approach combines Monte Carlo Simulation (MCS) with the RandSHARP metaheuristic, which was originally designed for solving the Capacitated Arc-Routing Problem with deterministic demands (CARP). The RandSHARP metaheuristic is a biased-random...

In this paper a flexible hybrid methodology, combining Ant Colony Optimisation (ACO) and Constraint Programming (CP), is presented for solving Vehicle Routing Problems (VRP). The stress of this methodology is on the word ‘flexible’: It gives reasonably good results to changing problems without high solution redesign efforts. Thus a different proble...

This paper presents a review of the literature on gamification design frameworks. Gamification, understood as the use of game design elements in other contexts for the purpose of engagement, has become a hot topic in the recent years. However, there's also a cautionary tale to be extracted from Gartner's reports on the topic: many gamification-base...

The concept of Smart City is entangled with urban transportation and mobility. Increasing density of urban living, and consequently growing commercial establishments, requires the development of sustainable efficient transportation systems able to deal with the movement of large quantities of goods and services for commercial and domestic use. The...

The Vehicle Routing Problem (VRP) is a well known research line in the optimisation research community. Its different basic variants have been widely explored in the literature. Even though it has been studied for years, the research around it is still very active. The new tendency is mainly focused on applying this study cases to real life problem...

This paper reviews the main concepts and existing literature related to the use of biased randomization of classical heuristics and the combination of simulation with meta-heuristics (Simheuristics) in order to solve complex combinatorial optimization problems, both of deterministic and stochastic nature, in the popular field of Vehicle and Arc Rou...

In non-smooth optimization problems the objective function to minimize or maximize is non-smooth and usually non-convex either, which is a frequent characteristic of real-life optimization problems. In this chapter we discuss the arc routing problem with a non-smooth cost function, and propose a randomized algorithm for solving it. Our approach emp...

This paper describes a simulation–optimization algorithm for the Permutation Flow shop Problem with Stochastic processing Times (PFSPST). The proposed algorithm combines Monte Carlo simulation with an Iterated Local Search metaheuristic in order to deal with the stochastic behavior of the problem. Using the expected makespan as initial minimization...

The main goal of this chapter is to present a hybrid scheme which combines classical heuristics with biased-randomization processes. As it will be discussed later, this hybrid scheme represents an efficient, relatively simple, and flexible way to deal with several Combinatorial Optimization Problems in different fields, even when considering realis...

The Vehicle Routing Problem with Time Windows is a NP-hard routing problem where the demand is located in nodes and should be completely served fulfilling certain scheduling constraints for delivering. This paper presents a randomized algorithm which combines a classical heuristic with biased random sampling in order to solve this type of problem....

Nowadays urban transportation is a strategic domain for distribution companies. In academic literature, this problem is categorized as a Vehicle Routing Problem, a popular research stream that has undergone significant theoretical advances but has remained far from practice implementations. In fact, a general combinatorial routing problem has emerg...

This paper proposes a heuristic algorithm for solving the scheduling of capacity requests and the periodic assignment of radio re-sources in a geostationary satellite network with a star topology. The network uses the Demand Assigned Multiple Access protocol in the link layer, and the Multi-Frequency Time Division Multiple Access (MF-TDMA) as well...

Urban transportation is a strategic domain that has become an important issue for client satisfaction in distribution companies. In academic literature, this problem is categorized as a Vehicle Routing Problem, a popular research stream that has undergone significant theoretical advances but has remained far from practice implementations. Most Vehi...

This paper proposes a new hybrid algorithm for solving the Arc Routing Problem with Stochastic Demands (ARPSD). Our approach combines Monte Carlo simulation (MCS) with the RandSHARP algorithm, which is designed for solving the Capacitated Arc Routing Problem (CARP) with deterministic demands. The RandSHARP algorithm makes use of a CARP-adapted vers...

The Capacitated Arc Routing Problem (CARP) is a combinatorial optimization problem similar to the well-known Capacitated Vehicle Routing Problem (CVRP). In the CARP, the customers' demands are located on the edges (arcs) of a general (not necessarily complete) graph. This is in contrast to the CVRP, where demand is located on the nodes of a complet...

After introducing the Vehicle Routing Problem with Stochastic Demands (VRPSD) and some related work, this paper proposes a flexible solution methodology. The logic behind this methodology is to transform the issue of solving a given VRPSD instance into an issue of solving a small set of Capacitated Vehicle Routing Problem (CVRP) instances. Thus, ou...

The Arc Routing Problem is a kind of NP-hard routing problems where the demand is located in some of the arcs connecting nodes and should be completely served fulfilling certain constraints. This paper presents a hybrid algorithm which combines a classical heuristic with biased random sampling, to solve the Capacitated Arc Routing Problem (CARP). T...

This paper presents an original hybrid approach to solve the Capacitated Vehicle Routing Problem (CVRP). The approach combines a Probabilistic Algorithm with Constraint Programming (CP) and Lagrangian Relaxation (LR). After introducing the CVRP and reviewing the existing literature on the topic, the paper proposes an approach based on a probabilist...

This paper presents the SR-GCWS-CS probabilistic algorithm that combines Monte Carlo simulation with splitting techniques and the Clarke and Wright savings heuristic to find competitive quasi-optimal solutions to the Capacitated Vehicle Routing Problem (CVRP) in reasonable response times. The algorithm, which does not require complex fine-tuning pr...

This paper presents a hybrid approach that aims at solving the Capacitated Vehicle Routing Problem (CVRP) by means of combining Constraint Programming (CP) with Lagrangian Relaxation (LR) and Probabilistic Algorithms. After introducing the CVRP and reviewing the main literature in this area, the paper proposes the use of a multistart hybrid Variabl...

Routing vehicles to serve customers is a problem that naturally arises in many distribution systems. Moreover, fleet management requires fast algorithms able to cope with continuously changing needs. Many efforts have been addressed to tackle different vehicle routing problem's variants. Among them, the pick up and delivery problem with time window...

Resumen En este artículo presentamos CUCKOO (QUality cheCKing of Object Oriented de-signs) una plataforma web para la verificación de diagramas de clases UML. Esta plataforma está orientada a facilitar el aprendizaje de las fases de análisis y diseño dentro de las asigna-turas de Ingeniería del Software.

The aim of this work is to present a simulation-based algorithm that not only provides a competitive solution for instances of the Capacitated Vehicle Routing Problem (CVRP), but is also able to efficiently generate a full database of alternative good solutions with different characteristics. These characteristics are related to solution's properti...

In current model-driven development approaches, software models are the primary artifacts of the development process. Therefore, assessment of their correctness is a key issue to ensure the quality of the final application. Research on model consistency has focused mostly on the models' static aspects. Instead, this paper addresses the verification...

Vehicle Routing Problems (VRPs) cover a wide range of well-known NP-hard problems where the aim is to serve a set of customers with a fleet of vehicles under certain constraints. Literature contains sev-eral approaches -coming from different fields like Operations Research, Artificial Intelligence and Computer Science-which try to get good (near-op...

In the MDD and MDA approaches, models become the primary artifacts of the development process. Therefore, assessment of the correctness of such models is a key issue to ensure the quality of the final application. In that sense, this paper presents an automatic method that uses the Constraint Programming paradigm to verify UML class diagrams extend...

L�evolució del World Wide Web (o simplement web) des del seu naixement a la dècada dels vuitanta del segle xx ha estat gegant. La incorporació de nous usuaris, exponencial en el temps, així com l�aportació constant de noves maneres d�organitzar les dades, comunicar-se, compartir informació, etc., han fet que el web hagi assolit en només dues dècade...

We present UMLtoCSP, a tool for the formal verification of UML/OCL models. Given a UML class diagram anno- tated with OCL constraints, UMLtoCSP is able to auto- matically check several correctness properties, such as the strong and weak satisfiability of the model or the lack of redundant constraints. The tool uses Constraint Logic Pro- gramming as...

This article presents an optimization methodology of batch production processes assembled by shared resources that rely on a mapping of state events into time events, allowing in this way the straightforward use of well-consolidated scheduling policies developed for manufacturing systems. A technique to generate the timed Petri net representation f...

Simulation models have proved to be useful for examining the performance of different system configurations and/or alternative operating procedures for complex logistic or manufacturing systems. However, when applying simulation techniques to increase the performance of those systems, several limitations arise due to their inability to evaluate mor...

The generic hoist scheduling problem is NP-hard and arises from automated manufacturing lines. In recent work using the constraint logic programming (CLP) formalism, a uni ed model has been developed with the problem description and solution method separated. We provide an improved model and new preprocessing stages where, as before, solutions and...

The generic hoist scheduling problem is NP-hard and arises from automated manufacturing lines. In recent work using the constraint logic programming (CLP) formalism, a unified model has been developed with the problem description and solution method separated. We provide an improved model and new preprocessing stages where, as before, solutions and...

The use of traditional production planning techniques is constrained by large numbers of decision variables, uncertainty in demand and time production, and nondeterministic system behaviour, characteristics intrinsic in manufacturing. The aim of this paper is to present a methodology that combines the modelling power of petri-nets (PN) to represent...

Traditional production planning techniques are constrained by large numbers of decision variables, uncertainty in demand and time production, and non-deterministic system behaviour (intrinsic characteristics in manufacturing). This paper presents an improvement to a methodology in the area of Knowledge Based Systems (KBS) which generates automatica...

Flexible manufacturing systems (FMS) have been taking a prominent place in production markets, but constant changes in production rates and product types force us to sort out constantly the scheduling problem that use to be NP-hard. Most commercial tools used to optimize FMS resources are analytical, and often limited to describing stationary relat...

The use of traditional production planning techniques is constrained by large num-bers of decision variables, uncertainty in demand and time production, and non-deterministic system behaviour, characteristics intrinsic in manufacturing. The aim of this paper is to present a methodology that combines the modelling power of petri-nets (PN) to represe...