Vinícius Amaral Armentano

Genetic local search for multi-objective flowshop scheduling problems

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 propose a genetic local search algorithm with features such as preservation of dispersion in the population, elitism, and use of a parallel multi-objective local search so as intensify the search in distinct regions. The concept of Pareto dominance is used to assign fitness to the solutions and in the local search procedure. The algorithm is applied to the flowshop scheduling problem for the following two pairs of objectives: (i) makespan and maximum tardiness; (ii) makespan and total tardiness. For instances involving two machines, the algorithm is compared with Branch-and-Bound algorithms proposed in the literature. For such instances and larger ones, involving up to 80 jobs and 20 machines, the performance of the algorithm is compared with two multi-objective genetic local search algorithms proposed in the literature. Computational results show that the proposed algorithm yields a reasonable approximation of the Pareto optimal set.

Tabu search for total tardiness minimization in flowshop scheduling problems

This work addresses the permutation flowshop scheduling problem with the objective of minimizing total tardiness. First, the behavior of solutions for small problems is analyzed for different due date scenarios. Then a tabu search-based heuristic is proposed as a method to explore the solution space. Diversification, intensification, and neighborhood restriction strategies are evaluated. Computational tests are presented and comparisons with the NEH algorithm and with a Branch-and-Bound algorithm are made. Scope and purpose Surveys of production scheduling show that meeting customer due dates is a critical concern for many manufacturing systems. While there is considerable research to minimize the makespan, very little work is reported on minimizing the total tardiness for scheduling jobs on a permutation flowshop. In this paper, we investigate the application of tabu search to this problem in order to obtain better solutions in a reasonable time. Special strategies are included to improve the performance of the method.

Tabu search with path relinking for an integrated production-distribution problem

This paper deals with the problem of integrating production and distribution planning over periods of a finite horizon. We consider a capacity-constrained plant that produces a number of items distributed by a fleet of homogenous vehicles to customers with known demand for each item in each period. The production planning defines the amount of each item produced in every period, while the distribution planning defines when customers should be visited, the amount of each item that should be delivered to customers, and the vehicle routes. The objective is to minimize production and inventory costs at the plant, inventory costs at the customers and distribution costs. We propose two tabu search variants for this problem, one that involves construction and a short-term memory, and one that incorporates a longer term memory used to integrate a path relinking procedure to the first variant. The proposed tabu search variants are tested on generated instances with up to ten items and on instances from the literature involving a single item.

Scatter search for project scheduling with resource availability cost

This paper considers a project scheduling problem with the objective of minimizing resource availability costs, taking into account a deadline for the project and precedence relations among the activities. Exact methods have been proposed for solving this problem, but we are not aware of existing heuristic methods. Scatter search is used to tackle this problem, and our implementation incorporates advanced strategies such as dynamic updating of the reference set, the use of frequency-based memory within the diversification generator, and a combination method based on path relinking. We also analyze the merit of employing a subset of different types when combining solutions. Extensive computational experiments involving more than 2400 instances are performed. For small instances, the performance of the proposed procedure is compared to optimal solutions generated by an exact cutting plane algorithm and upper and lower bounds from the literature. For medium and larger size instances, we developed simple multi-start heuristics and comparative results are reported.

The pencil ( sE–A ) and controllability-observability for generalized linear systems: a geometric approach

In this paper we adopt a geometric approach to study the pencil (sE-A). The relationship between a certain subspace and a polynomial basis for ker (sE-A) is established. An alternative characterization for the finite-zero structure of a singular pencil is presented. Necessary and sufficient conditions for the columns or the rows of the singular pencil (sE-A) to be linearly independent over the ring of the polynomials are also given. The main geometric properties of a regular pencil are presented, including the identification of the subspace in which the impulsive response of the autonomous generalized linear system Ex = Ax takes place. The generalized linear system Ex = Ax + Bu; y = Cx is also considered: necessary and sufficient conditions for the infinite-zeros of the regular pencil (sE-A) to be controllable and observable are shown.

Lower bounding schemes for flowshops with blocking in-process

While there is a considerable amount of research that deals with a flowshop with no storage constraints, few works have addressed the flowshop with blocking in-process. Scheduling problems with blocking arise in serial manufacturing processes where no intermediate buffer storage is available. This paper proposes a lower bound, which exploits the occurrence of blocking, on the total tardiness of the jobs. Its efficiency is evaluated using a branch-and-bound algorithm on several problems. A lower bound on the makespan is also derived and computational tests are presented.

Tabu search for minimizing total tardiness in a job shop

Abstract This paper presents a tabu search approach to minimize total tardiness for the job shop scheduling problem. The method uses dispatching rules to obtain an initial solution and searches for new solutions in a neighborhood based on the critical paths of the jobs. Diversification and intensification strategies are suggested. For small problems the solutions’ quality is evaluated against optimal solution values and for large problems the tabu search performance is compared with two heuristics proposed in the literature.

A Lagrangian-based heuristic for the capacitated lot-sizing problem in parallel machines

This paper addresses the capacitated lot-sizing problem involving the production of multiple items on unrelated parallel machines. A production plan should be determined in order to meet the forecast demand for the items, without exceeding the capacity of the machines and minimize the sum of production, setup and inventory costs. A heuristic based on the Lagrangian relaxation of the capacity constraints and subgradient optimization is proposed. Initially, the heuristic is tested on instances of the single machine problem and results are compared with heuristics from the literature. For parallel machines and small problems the heuristic performance is tested against optimal solutions, and for larger problems it is compared with the lower bound provided by the Lagrangian relaxation.

Tardiness minimization in a flexible job shop: A tabu search approach

This paper addresses the problem of scheduling jobs in a flexible job shop with the objective of minimizing total tardiness. The flexible job shop differs from the classical job shop in that each of the operations associated with a job can be processed on any of a set of alternative machines. Two heuristics based on tabu search are developed for this problem: a hierarchical procedure and a multiple start procedure. The procedures use dispatching rules to obtain an initial solution and then search for improved solutions in neighborhoods generated by the critical paths of the jobs in a disjunctive graph representation. Diversification strategies are also implemented and tested. The outcomes of extensive computational results are reported.

Eigenvalue placement for generalized linear systems

This paper deals with some aspects of eigenvalue placement by state feedback for generalized linear systems described by E = Ax + Bu , where E is a singular map. It is shown that controllability of the infinite eigenvalues of the pencil ( sE − A ) is equivalent to the existence of a state feedback map which assigns those eigenvalues to pre-specified complex numbers. A procedure for the assignment of all eigenvalues to distinct complex numbers is also discussed.