Pedro Jesús Copado Méndez

Pedro Jesús Copado Méndez
Universitat Oberta de Catalunya | UOC · Computer, Multimedia and Telecommunication Studies

Doctor of Philosophy

About

39
Publications
4,229
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
150
Citations
Citations since 2017
31 Research Items
121 Citations
201720182019202020212022202301020304050
201720182019202020212022202301020304050
201720182019202020212022202301020304050
201720182019202020212022202301020304050
Additional affiliations
May 2019 - May 2019
Universitat Oberta de Catalunya
Position
  • Research Junior
November 2010 - June 2013
Universitat Rovira i Virgili
Position
  • Professor (Assistant)
Description
  • teaching support in Fonaments Matemàtics de l'Enginyeria I and II
October 2009 - present
Universitat Rovira i Virgili
Position
  • PhD Student

Publications

Publications (39)
Chapter
This paper presents a K-Prototype assisted hybrid heuristic approach called SLIM+KP for solving large instances of the Train Unit Scheduling Optimization (TUSO) problem. TUSO is modelled as an Integer Multi-commodity Flow Problem (IMCFP) based on a Directed Acyclic Graph (DAG). When the problem size goes large, the exact solver is unable to solve i...
Conference Paper
This paper presents a K-Prototype assisted hybrid heuristic approach called SLIM+KP for solving large instances of the Train Unit Scheduling Optimization (TUSO) problem. TUSO is modelled as an Integer Multi-commodity Flow Problem (IMCFP) based on a Directed Acyclic Graph (DAG). When the problem size goes large, the exact solver is unable to solve i...
Article
Full-text available
Train unit scheduling assigns vehicles to cover all trips of a fixed timetable satisfying constraints such as seat demands. With a two-phase approach, this problem is first solved in Phase I as an integer multi-commodity flow problem. Train stations are simplified as single points and coupling orders of train units are left undetermined. In this pa...
Article
Full-text available
Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneous jobs are processed by a number of machines. The route that each job has to follow depends upo...
Article
Looking for an accurate and cost-effective solution to measure feed inventories, forecast the feed demand and allow feed suppliers to optimize inventories, production batches, and delivery routes.
Data
Data for this paper: Solving Hybrid Flow Shop Problem with priority restrictions in Semiconductor Manufacturing by Biased-Randomized Discrete-Event Heuristics
Conference Paper
Full-text available
Based on a real-life use-case, this paper discusses a manufacturing scenario where different jobs be processed by a series of machines. Depending on its type, each job must follow a pre-defined route in the hybrid flow shop, where the aggregation of jobs in batches might be required at several points of a route. This process can be modeled as a hyb...
Article
Full-text available
With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens’ mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours,...
Article
Full-text available
In the context of logistics and transportation, this paper discusses how simheuristics can be extended by adding a fuzzy layer that allows us to deal with complex optimization problems with both stochastic and fuzzy uncertainty. This hybrid approach combines simulation, metaheuristics, and fuzzy logic to generate near-optimal solutions to large sca...
Article
Full-text available
Purpose For any given customer, his/her profitability for a business enterprise can be estimated by the so-called customer lifetime value (CLV). One specific goal for many enterprises consists in maximizing the aggregated CLV associated with its set of customers. To achieve this goal, a company uses marketing resources (e.g. marketing campaigns), w...
Chapter
This chapter describes a case study regarding the use of ‘agile’ computational intelligence for supporting logistics in Barcelona’s hospitals during the COVID-19 crisis in 2020. Due to the lack of sanitary protection equipment, hundreds of volunteers, the so-called “Coronavirus Makers” community, used their home 3D printers to produce sanitary comp...
Article
Full-text available
The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that...
Article
Full-text available
The growth of e-commerce and the on-demand economy in urban and metropolitan areas has been accelerated by the recent COVID-19 pandemic. As a consequence, logistics and transportation operators are subject to a noticeable pressure to develop efficient delivery systems. These systems are also influenced by the global trend towards more sustainable t...
Article
Operational problems in agri-food supply chains usually show characteristics that are scarcely addressed by traditional academic approaches. These characteristics make an already NP-hard problem even more challenging; hence, this problem requires the use of tailor-made algorithms in order to solve it efficiently. This work addresses a rich vehicle...
Article
Full-text available
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...
Article
Full-text available
Advances in information and communication technologies have made possible the emergence of new shopping channels. The so-called 'omnichannel' retailing mode allows customers to shop for products online and receive them at home. This paper focuses on the omnichannel delivery concept for the retailing industry, which addresses the replenishment of a...
Article
Full-text available
In this paper we discuss the team orienteering problem (TOP) with dynamic inputs. In the static version of the TOP, a fixed reward is obtained after visiting each node. Hence, given a limited fleet of vehicles and a threshold time, the goal is to design the set of routes that maximize the total reward collected. While this static version can be eff...
Conference Paper
Full-text available
Train unit scheduling assigns vehicles to cover all the trips of a fixed timetable satisfying seat demands at minimum operational costs. Solved as a network flow problem, train stations are simplified to single points where certain station operation details are ignored. For instance, when a trip is covered by coupled train units, the coupling order...
Conference Paper
In this research is presented an hybrid approach based on heuris- tics for solving large instances for the Train Unit Scheduling Optimization (TUSO). TUSO has been modelled as an IntegerMulti-Commodity Flow Problem (IMCF) lay on a Directed Acyclic Graph (DAG), and solved by Integer Linear Programming (ILP). This method proceeds in a way to iterativ...
Conference Paper
Full-text available
We propose a branch-and-price-and-cut method with warm-start for solving the integer fixed-charge multicommodity flow (IFMCF) model for the network flow level of the train unit scheduling problem, in particular with complex minimum turnround time requirements. This problem is regarded to be difficult due to its nature in integer flows and fixed-cha...
Conference Paper
In this work, we are developing a hybrid method driving a core ILP solver with an iterative heuristic for the train unit scheduling optimization problem, which is formulated as an integer multi-commodity flow problem. This approach aims at reducing the problem to a minimal size but still retaining all the essential components for an optimal solutio...
Article
The ϵ-constraint method is an algorithm widely used to solve multi-objective optimization (MOO) problems. In this work, we improve this algorithm through its integration with rigorous dimensionality reduction methods and pseudo/quasi-random sequences. Numerical examples show that the enhanced algorithm outperforms the standard ϵ-constraint method i...
Article
Full-text available
Large neighborhood search is a popular hybrid metaheuristic which results from the use of a complete techniquesuch as dynamic programming, constraint programming or MIP solversfor finding the best neighbor within a large neighborhood of the incumbent solution. In this work we present an application of large neighborhood search to a strategic supply...
Article
Multi-objective optimization (MOO) is an effective technique for studying optimal trade-off solutions that balance several criteria. The main limitation of MOO is that its computational burden grows in size with the number of objectives. With the goal to overcome this computational barrier, this work introduces a new algorithm for reducing the numb...

Questions

Question (1)
Question
We have developed a queue model using anylogic and we would like to integrate with optimization program implemented in Java. Could we call it from Java in the Anylogic Cloud?

Network

Cited By

Projects

Projects (2)
Project
Make the train unit schedules be more operable at station level.
Project
Train Units Scheduling Optimization