This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach ...

This paper presents new, carefully designed algorithms for five biobjective permutation flow shop scheduling problems that arise from the pairwise combinations of the objectives (i) makespan, (ii) the sum of the completion times of the jobs, and (iii) both, the weighted and nonweighted total tardiness of all jobs. The proposed algorithm combines two search methods, two-phase local search and Pa...

Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...

the aim of this paper is to study a multi-product, multi-period production systems in a hybrid flow shop so that lot-sizing and scheduling will be detemined simultaneously. a new mixed-integer programming model is proposed to formulate the studied problem. the objective function in this investigation includes the total cost of production, inventory and external supply. in the case of not satisf...

This paper develops a new VNS approach to Permutational Flow shop Scheduling Problem with Total Flow time criterion. There are many hybrid approaches in the problem’s literature, that make use of VNS internally, usually applying job insert neighbourhood followed by job interchange neighbourhood. In this study different ways to combine both neighbourhoods were examined. All tests use the benchma...

A frequently occurring operational problem is one of processing a given number of jobs (commodities) on a specified number of machines (facilities) referred to by various investigators as scheduling, dispatching, sequencing, or combinations thereof (Gupta and Stafford, 2006). In most manufacturing environments, a set of processes is needed to be serially performed in several stages before a job...

This paper presents the application of self organinsing migration algorithm (SOMA) to the scheduling problem of flow shop. Flow shop is regarded as the most widely utilized shop management system. Two different benchmark problems are attempted with good results obatined both in comparison with the optimal and other published heuristics. INTRODUCTION Advanced manufacturing systems often rely on ...

This paper addresses the multistage hybrid flow shop (HFS) scheduling problems. The HFS is the special case of flowshop problem. Multiple parallel machines are considered in each stage in the HFS. The HFS scheduling problem is known to be strongly NPhard. Hence, many researchers proposed metaheuristic algorithms for solving the HFS scheduling problems. This paper develops a bat algorithm (BA) t...

in this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all work centers. this study seems utterly new and it is applicable to any performance measure based on the completion time. the in...