Jose Elias CLAUDIO Arroyo

Universidade Federal de Viçosa (UFV) | UFV · Departamento de Informática

This paper considers the Flow shop Sequence Dependent Group Scheduling (FSDGS) problem with minimization of total flow time criterion. In this problem, the n jobs to be processed on m machines are grouped in families (groups) in a way that a machine setup time is needed between two consecutive jobs of different groups. The FSDGS problem is classifi...

to build and maintain software is a complex task. To manage all involved variables is a tough activity and it gets less difficult when the work is managed as a process. No concrete evidence was found of the existence of a "perfect" software development process and thus adapting process models to the realities faced by development teams is a potenti...

This work treats the single machine scheduling problem in which the setup time depends on the sequence and the job family. The objective is to minimize the makespan and the total weighted tardiness. In order to solve the problem, two multi-objective algorithms are analyzed: one based on Multi-objective Variable Neighborhood Search (MOVNS) and anoth...

In this work we deal with a vehicle loading problem where a heterogeneous fleet of vehicles must be loaded with a set of items. Differently from the traditional vehicle loading problems, there is also a set of optional items that may be loaded in order to maximize the used capacity of the selected vehicles. The problem is decomposed in two subprobl...

In wireless sensors networks (WSNs) the efficient use of the sensors' energy is a key point to extend the network lifetime and has been the center of attention by many researchers. There are several different techniques to reduce the sensor's energy consumption. Sensor node clustering is one of these techniques. However, finding an optimal clusteri...

In wireless sensors networks (WSNs) the efficient use of the sensors' energy is a key point to extend the network lifetime. In the literature there are several different techniques to reduce the energy consumption of the sensors. Sensor node clustering is one of these techniques commonly used. However, finding an optimal clustering in WSNs is a NP-...

This work treats the single machine scheduling problem in which the setup time depends on the sequence and the job family. The objective is to minimize the makespan and the total tardiness. In order to solve the problem two multi-objective algorithms are analyzed: one based on Multi-objective Variable Neighborhood Search (MOVNS) and another on Pare...

This paper addresses the parallel machine scheduling problem which consists in the assignment of n jobs on m identical machines with the objective of minimizing the total tardiness of the jobs using the job splitting property. In this problem is assumed that a job can be split into sub-jobs and these sub-jobs can be processed independently on paral...

This paper presents a hybrid metaheuristic for the single vehicle routing problem with deliveries and selective pickups (SVRPDSP). A vehicle departs loaded from the depot, visit every customer delivering a certain amount of goods according to their demand, and optionally pickup items from those customers, receiving a profit for each pickup realized...

In this paper, we compare three multi-objective algorithms based on Variable Neighborhood Search (VNS) heuristic. The algorithms are applied to solve the single machine scheduling problem with sequence dependent setup times and distinct due windows. In this problem, we consider minimizing the total weighted earliness/tardiness and the total flowtim...

In this paper, we analyze the performance of two multi-objective algorithms based on the Variable Neighborhood Search (VNS). The first algorithm was proposed by Geiger and the second algorithm is proposed in this work. The algorithms are applied to solve the single machine scheduling problem with sequence dependent setup times and distinct due wind...

The importance of studying the immune system comes mainly from its fundamental function in the maintenance of human life and its health. In order to help elucidating such a complex process, computational models for the immune system are applied by researchers to verify important hypotheses in a much cheaper and faster way when compared to in-vivo i...

This paper presents a multi-objective greedy randomized adaptive search procedure (GRASP)-based heuristic for solving the permutation flowshop scheduling problem in order to minimize two and three objectives simultaneously: (1) makespan and maximum tardiness; (2) makespan, maximum tardiness, and total flowtime. GRASP is a competitive metaheuristic...

In this paper, we examine the p-median problem from a bi-objective point of view. Since this is a NP-Hard problem, an efficient algorithm based on the Iterated Local Search heuristic (ILS) is proposed to determine non-dominated solutions (an approximation of the Pareto-optimal solutions). ILS is a simple and powerful stochastic method that has show...

In this paper, we describe and show the results of a combination of two metaheuristics to solve an unrelated parallel machines scheduling problem in which the setup times depend not only on the machine and job sequence, but also on the amount of resource assigned. This problem has been proposed recently on the literature and since then a couple of...

This paper considers the p-median problem that consists in finding p-locals from a set of m candidate locals to install facilities minimizing simultaneously two functions: the sum of the distances from each customer to its nearest facility and the sum of costs for opening facilities. Since this is a NP-Hard problem, heuristic algorithms are the mos...

This paper deals with the a bi-objective p-median problem that consists in finding p-locals from a set of m candidate locals to install facilities in which two objective functions are simultaneously minimized: the sum of the distances from each customer to its nearest facility and the sum of costs for opening facilities. To determine a set of non-d...

This paper presents a combination of evolutionary algorithm and mathematical programming with an efficient local search procedure for a just-in-time job-shop scheduling problem (JITJSSP). Each job on the JITTSSP is composed by a sequence of operations, each operation having a specific machine where it must be scheduled and a due date when it should...

This paper addresses the unrelated parallel machine problem with machine and job sequence dependent setup. In this problem, the amount of the setup time does not only depend on the machine and job sequence, but also on a number of resources assigned, which can vary between a minimum and a maximum. The goal is to find a schedule that minimizes the l...

This paper describes a successful combination of genetic algorithm and local search procedure to find good solutions for just-in-time job-shop scheduling problem with earliness and tardiness penalties. For each job is given a specific order of machines in which its operations must be processed, and each operation has a due date, a processing time,...

This paper addresses an unrelated parallel machine problem with machine and job sequence dependent setup times. The objective function considered is a linear combination of the total completion time and the total number of resources assigned. Due to the combinatorial complexity of this problem, we propose an algorithm based on the GRASP metaheurist...

In this paper the NP-hard problem of scheduling jobs in a single machine with sequence dependent setup times is considered with the objective of minimizing the total tardiness with respect to the due dates. An Iterative Local Search (ILS) heuristic is proposed which uses a GRASP (Greedy Randomized Adaptive Search Procedure) algorithm to generate an...

This article describes a combination of genetic algorithm and local search for the just-in-time job- shop scheduling problem, with earliness and tardiness penalties. In this problem, each operation of each job has a specific machine to be processed in a specific order and a process time, a due date, and earliness and tardiness costs, which will be...

This article considers the bi-objective Job Shop Scheduling Problem in which the make span and the total tardiness of jobs are minimized. In order to find a set of dominant solutions, that is, an approximation of the Pareto optimal solutions, we propose three versions of a genetic algorithm with techniques like hybridization with local search, path...

This study considers a single machine scheduling problem with the objective of minimizing the total weighted tardiness of the jobs. This problem is one of the most famous problems in single machine scheduling theory and it is NP-hard. In this paper, we propose a hybrid heuristic which combines GRASP with Path Relinking to find good quality solution...

This paper considers the permutation flowshop scheduling problem with blocking in-process with the objective of minimizing the total tardiness of jobs. In this problem there are no buffers between successive machines, that is, it is not allowed intermediate queues of jobs waiting in the system for their next operations. To solve the problem, we pro...

This paper proposes a GRASP (Greedy Randomized Adaptive Search Procedure) algorithm for the multi-criteria minimum spanning tree problem, which is NP-hard. In this problem a vector of costs is defined for each edge of the graph and the problem is to find all Pareto optimal or efficient spanning trees (solutions). The algorithm is based on the optim...

This paper considers the permutation flowshop scheduling problem with blocking in-process with the objective of minimizing the total tardiness of jobs. In this problem there are no buffers between successive machines, that is, it is not allowed intermediate queues of jobs waiting in the system for their subsequent operations. To solve the problem,...

Este artigo propõe diferentes estratégias de paralelização de um algoritmo GRASP (Greedy Randomized Adaptive Search Procedure) multicritério. O algoritmo paralelo proposto é aplicado ao problema da árvore geradora mínima multicritério, que é NP-difícil. Neste problema, um vetor de custos é definido para cada aresta do grafo e o objetivo é encontrar...

RESUMO Este artigo aborda o problema de posicionamento de antenas de telecomunicações (por exemplo, antenas de transmissão de sinais de rádio-difusão, sinais de TV, Internet via rádio, etc) em pontos específicos de uma região (cidade). O objetivo é atender ou cobrir a maior quantidade de pontos de demanda usando um número mínimo de antenas. São con...

This paper addresses flowshop scheduling problems with multiple performance criteria in such a way as to provide the decision maker with approximate Pareto optimal solutions. Genetic algorithms have attracted the attention of researchers in the nineties as a promising technique for solving multi-objective combinatorial optimization problems. We pro...

This paper proposes different strategies of parallelizing a multi-criteria GRASP (greedy randomized adaptive search problem) algorithm. The parallel GRASP algorithm is applied to the multi-criteria minimum spanning tree problem, which is NP-hard. In this problem, a vector of costs is defined for each edge of the graph and the goal is to find all th...

This paper proposes a new tabu search algorithm for multi-objective combinatorial problems with the goal of obtaining a good approximation of the Pareto-optimal or efficient solutions. The algorithm works with several paths of solutions in parallel, each with its own tabu list, and the Pareto dominance concept is used to select solutions from the n...

This paper addresses the flowshop scheduling problem with multiple performance objectives in such a way as to provide the decision maker with approximate Pareto optimal solutions. It is well known that the partial enumeration constructive heuristic NEH and its adaptations perform well for single objectives such as makespan, total tardiness and flow...

In this article, we propose a greedy randomized adaptive search procedure (GRASP) to generate a good approximation of the efficient or Pareto optimal set of a multi-objective combinatorial optimization problem. The algorithm is based on the optimization of all weighted linear utility functions. In each iteration, a preference vector is defined and...

This work deals with the parallel machine scheduling problem with resource-assignable sequence dependent setup times. The goal of the problem is to minimize the total completion time and the total assignes resources. Due to the combinatorial complexity of this problem, an algorithm based on heuristic GRASP is proposed, in which the randomness param...

Resumo Este artigo apresenta um algoritmo genético com estratégias de busca local para resolver o problema de escalonamento de tarefas em máquinas paralelas idênticas. São consideradas datas de entrega das tarefas e tempos de preparação dependentes da seqüência. O problema consiste em determinar a ordem de processamento das tarefas nas máquinas, mi...

RESUMO Este artigo propõe uma heurística GRASP para resolver de forma aproximada o problema de Roteamento de Veículos com Coleta e Entrega Simultânea. Este problema é uma variante do problema clássico de roteamento de veículos na qual cada cliente faz ao mesmo tempo dois tipos de pedidos: coleta e entrega, e a carga do veículo em qualquer rota é um...

This paper addresses the identical parallel machine scheduling problem with sequence dependent setup times. This problem consists in determining the job order sequence on each machine minimizing simultaneously two criteria: maximum completion time (makespan) and the total job tardiness with relation to due dates. This problem has a set of solutions...