Disruption on a supply chain provokes lost that should be minimized looking for alternative suppliers. This solution involves a strategy to manage the impact of the disruption and thus to recuperate the supply chain. Difficulty of the management is the diversity of involved factors such that turns complex to provide or choice a solution among the possible ones. Depending on the objective(s) to ...

The Strength Pareto Evolutionary Algorithm (SPEA) (Zitzler and Thiele 1999) is a relatively recent technique for finding or approximating the Pareto-optimal set for multiobjective optimization problems. In different studies (Zitzler and Thiele 1999; Zitzler, Deb, and Thiele 2000) SPEA has shown very good performance in comparison to other multiobjective evolutionary algorithms, and therefore it...

This paper presents a Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for the optimal operation of a complex multipurpose and multi-reservoir system. Firstly, MOEA/D decomposes a multi-objective optimization problem into a number of scalar optimization sub-problems and optimizes them simultaneously. It uses information of its several neighboring sub-problems for optimizin...

Under mild conditions, it can be induced from the Karush-Kuhn-Tucker condition that the Pareto set, in the decision space, of a continuous multiobjective optimization problem is (m− 1)-D piecewise continuous, where m is the number of objectives. Based on this regularity property, we propose a Regularity Model based Multiobjective Estimation of Distribution Algorithm (RM-MEDA) for continuous mul...

Constrained multiobjective optimization arises in many real-life applications, and is therefore gaining a constantly growing attention of the researchers. Constraint handling techniques differ in the way infeasible solutions are evolved in the evolutionary process along with their feasible counterparts. Our recently proposed threshold based penalty function gives a chance of evolution to infeas...

With the deepening of “source-load-storage” interaction and development demand response technology, emergence prosumers has led to new vitality potential for optimal operation microgrids. By implementing a mechanism prosumers, peak shaving valley filling are realized, load fluctuations balanced. However, high costs investing operating energy storage system (ESS) restrict their ability participa...

The Genetic Immune Strategy for Multiple Objective Optimization (GISMOO) is a hybrid algorithm for solving multiobjective problems. The performance of this approach has been assessed using a classical combinatorial multiobjective optimization benchmark: the multiobjective 0/1 knapsack problem (MOKP) [1] and two-dimensional unconstrained multiobjective problems (ZDT) [2]. This paper shows that t...

49 Any real-world optimization problem involves several objectives. Chemical engineering is no exception. Chemical processes, such as distillation (Figure 1), refinery operations, polymerization, etc., involve a number of process parameters which are to be set for achieving certain properties in the final product. Often such a process is modelled using a number of differential and/or algebraic ...