We consider a multi-location inventory system where inventory choices at each location are centrally coordinated through the use of lateral Transshipments. This cooperation between different locations of the same echelon level often leads to cost reduction and service level improvement. However, when some locations face embarrassing storage capacity limits, inventory sharing through transshipme...

The aim of the present work is to use multi-objective evolutionary algorithms (MOEA) to parametrise an ecological assembly model based on Lotka-Volterra dynamics. In community assembly models, species are introduced from a pool of species according to a sequence of invasion. By manipulating the assembly sequences, we look at the structure of the final communities obtained by a multi-objective p...

In this paper, a new genetic algorithm for multi-objective optimization problems is introduced. That is called “Local Cultivation GA (LCGA)”. LCGA has a neighborhood crossover mechanism in addition to the mechanism of GAs that had proposed in the past researches. As compared with SPEA2, NSGA-II, and MOGA, LCGA is the robust algorithm which should find the Pareto optimum solution. Since LCGA is ...

in this study, a two-objective mixed-integer linear programming model (milp) for multi-product re-entrant flow shop scheduling problem has been designed. as a result, two objectives are considered. one of them is maximization of the production rate and the other is the minimization of processing time. the system has m stations and can process several products in a moment. the re-entrant flow sho...

Convergence analyses of evolutionary multiobjective optimization algorithms typically deal with the convergence in limit (stochastic convergence) or the run time. Here, for the first time concrete results for convergence rates of several popular algorithms on certain classes of continuous functions are presented. We consider the algorithms in the version of using a (1+1) selection scheme. Then,...

The Combined Heat and Power Economic Emission Load Dispatch (CHPEED) is an optimization problem to minimize the cost and emission while ensuring the fulfilling the power and heat demand and feasible constraints. This paper presents Particle Swarm Optimization (PSO) technique and other to solve CHPEED with bounded feasible operating region. The main potential of this technique is that it proper ...

In this paper we describe a solution for the Transformation Tool Contest 2016 (TTC’16) Class Responsibility Assignment (CRA) case study using Sigma, a family of Scala internal Domain-Specific Languages (DSLs) that provide an expressive and efficient API for model consistency checking and model transformations. Since the Class Responsibility Assignment problem is a search-based problem, we base ...

In the paper, a novel stochastic Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA). In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MO...