Capabilities of enhanced simulated-annealing-based algorithms in solving process planning problems in reconfigurable manufacturing are investigated. The algorithms are enhanced by combining variants of the simulated annealing technique with other algorithm concepts such as (i) knowledge exploitation and (ii) parallelism. Four configurations of simulated annealing algorithms are devised and enga...

This paper considers the allocation of maximum reliability to a complex system, while minimizing the cost of the system, a type of multi-objective optimization problem (MOOP). Multi-objective Evolutionary Algorithms (MOEAs) have been shown in the last few years as powerful techniques to solve MOOP .This paper successfully applies a Nondominated sorting genetic algorithm (NSGA-II) technique to o...

As multiobjective optimization problems have many solutions, evolutionary algorithms have been widely used for complex multiobjective problems instead of simulated annealing. However, simulated annealing also has favorable characteristics in the multimodal search. We developed several simulated annealing schemes for the multiobjective optimization based on this fact. Simulated annealing and evo...

introduction several methods have been developed to aid in selecting a network of biodiversity protected areas. one of these methods is artificial intelligence which includes a number of different computer algorithms that use an objective function to find the best solution. an algorithm is a mathematical process or a set of rules used for problem solving. recently, site selection algorithms hav...

Automatic synthesis of software architecture has already been shown to be feasible with genetic algorithms. A natural problem is to augment – if not replace – genetic algorithms with some other search methods in the process of searching good architectures. The present paper studies the possibilities of using simulated annealing for synthesizing software architecture. We start from functional re...

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population o...

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic ...

We describe a method to approximate a closed surface triangulation using simulated annealing. Our approach guarantees that all vertices and triangles in an approximating surface triangulation are within a user-de ned distance of the original surface triangulation. We introduce the idea of atomic envelopes to guarantee error bounds that are independent of the surface geometry. Atomic envelopes a...

To design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelated decisions involved in the design of a CMS. This paper provides an extensive coverage of important manufacturing features u...