this paper considers the job scheduling problem in virtual manufacturing cells (vmcs) with the goal of minimizing two objectives namely, makespan and total travelling distance. to solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (nsga-ii) and knowledge-based non-dominated sorting genetic algorithm (kbnsga-ii). the difference between these algor...

Optimizing the database queries is one of hard research problems. Exhaustive search techniques like dynamic programming is suitable for queries with a few relations, but by increasing the number of relations in query, much use of memory and processing is needed, and the use of these methods is not suitable, so we have to use random and evolutionary methods. The use of evolutionary methods, beca...

There exist two formulations of rough sets: the conceptual and computational one. The conceptual or semantical approach of rough set theory focuses on the meaning and interpretation of concepts, while algorithms to compute those concepts are studied in the computational formulation. However, the research on the former is rather limited. In this paper, we focus on a semantically sound approach o...

this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules.  in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...

Scheduling for a two-stage production system is one of the most common problems in production management. In this production system, a number of products are produced and each product is assembled from a set of parts. The parts are produced in the first stage that is a fabrication stage and then they are assembled in the second stage that usually is an assembly stage. In this article, the first...

In this paper, we introduce the concept of non-dominance (commonly used in multiobjective optimization) as a way to incorporate constraints into the tness function of a genetic algorithm. Each individual is assigned a rank based on its degree of dominance over the rest of the population. Feasible individuals are always ranked higher than infeasible ones, and the degree of constraint violation d...

Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters with it, this is why in recent decades extensive researches have been done on scheduling issues. A type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical ...

The Grouping Genetic Algorithm (GGA) is a Genetic Algorithm heavily modified to suit the structure of grouping problems. Those are the problems where the aim is to find a good partition of a set, or to group together the members of the set. The Bin Packing Problem (BPP) is a well known NP-hard grouping problem items of various sizes have to be grouped inside bins of fixed capacity. On the other...