Roman Anselmo Mora Gutiérrez

Solving electoral zone design problems with NSGA-II: application to redistricting in Mexico

The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes, in such a way that federal or state requirements are fulfilled. In Mexico, both population equality and compactness of the designed districts are considered as two conflicting objective functions. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (the NSGA-II) to this hard combinatorial problem, whereas the Mexican Federal Electoral Institute has traditionnally used a Simulated Annealing (SA) algorithm based on a weighted aggregation function. Despite some convergence troubles, the NSGA-II obtains promising results when compared with the SA algorithm, producing better-distributed solutions over a wider-spread front.

A heuristic algorithm based on tabu search for the solution of flexible job shop scheduling problems with lot streaming

The Job Shop Scheduling Problem (JSSP) has received a great attention from operation research and metaheuristic communities, because it constitutes a challenging optimization problem with many real-world applications. In this work, an extension of the simple JSSP operating mode is introduced, including flexibility (operations can be processed by several machines) and lot streaming (jobs may be divided into sublots). An integer programming model is developed in this study for tackling the resulting FJSSP-LS. This model was implemented within a a commercial solver, GUROBI and additionally, a Tabu Search (TS) algorithm is proposed as a solution technique. Compared over a set of 48 instances adapted for the FJSSP-LS working mode, the TS heuristic clearly outperforms the upper bounds found by GUROBI, which is never able to converge to optimality in a one hour time limit. Moreover, result analysis enables to provide some insights and draw some guidelines regarding the use of flexibility and lot streaming within JSSP.

Extension of the Method of Musical Composition for the Treatment of Multi-objective Optimization Problems

This work proposes a new technique for the treatment of Multi-objective Optimization Problems (MOPs), based on the extension of a socio-cultural algorithm, the Method of Musical Composition (MMC). The MMC uses a society of agents, called composers, who have their own creative ability, maintain a memory of their previous artwork and are also able to exchange information.

Aplicación del método de composición musical al problema de asignación de unidades de enseñanza y aprendizaje

Resumen es: El problema de horarios en instituciones educativas tiene una complejidad computacional que dificulta la obtencion de respuestas mediante el uso de metod...

A discrete artificial bee colony algorithm for the multi-objective redistricting problem

In this paper, the performance of two classical algorithms (simulated annealing and a discrete artificial bee colony) are compared on the redistricting problem, using a real example in Mexico and highlighting the superiority of the latter.