Due to the combinatorial explosions in solution space for scheduling problems, the balance between genetic search and local search is an important issue when designing a memetic algorithm [23] for scheduling problems. The main motivation of this research is to resolve the combinatorial explosion problem by reducing the possible neighborhood combinations using guided operations to remove these i...

the recent years have witnessed an increasing attention to the methods of multiple attribute decision making in solving the problems of the real world due to their shorter time of calculation and easy application. one of these methods is the ‘permutation method’ which has a strong logic in connection with ranking issues, but when the number of alternatives increases, solving problems through th...

Facility location decisions play a prominent role in strategic planning of many firms, companies and governmental organizations. Since in many real-world facility location problems, the data are subject to uncertainty, in this paper, we consider the P-center problem under uncertainty of demands. Using Bertsimas and Sim approach, we develop a robust model of the problem as an integer programming...

Abstract The connection between production scheduling and transportation is getting closer in smart manufacturing system, both of those problems are summarized as NP-hard problems. However, only a few studies have considered them simultaneously. This paper solves the integrated problem (IPTSP) hybrid flow shops, which an extension shop (HFSP). In addition to on machines, process automated guide...

A Memetic Algorithm (MA) encompasses a class of approaches with proven practical success in variety of optimization problems aiming to make use of benefits of each individual approach. In this paper, we present a special designed Memetic Algorithm to solve the well-known Symmetric Traveling Salesman Problem (STSP).The main feature of the Memetic Algorithm is to use a local search combined with ...

response surface methodology is a common tool in optimizing processes. it mainly concerns situations when there is only one response of interest. however, many designed experiments often involve simultaneous optimization of several quality characteristics. this is called a multiresponse surface optimization problem. a common approach in dealing with these problems is to apply desirability funct...

One of the fastest growing areas of evolutionary algorithm research is the enhancement of genetic algorithms by combination with local search methods or memes: often known otherwise as memetic algorithms. However there is often little theoretical basis on which to characterize the choice of memes that lead to successful memetic algorithm performance. In this paper, we investigate empirically th...