کار انعطاف پذیر-برنامه ریزی فروشگاه با مسیر یابی انعطاف پذیر و زمان راه اندازی جدا از هم با استفاده از روش بهینه سازی کلونی مورچه ها

This paper proposes an ant colony optimisation-based software system for solving FMS scheduling in a job-shop environment with routing flexibility, sequence-dependent setup and transportation time. In particular, the optimisation problem for a real environment, including parallel machines and operation lag times, has been approached by means of an effective pheromone trail coding and tailored ant colony operators for improving solution quality. The method used to tune the system parameters is also described. The algorithm has been tested by using standard benchmarks and problems, properly designed for a typical FMS layout. The effectiveness of the proposed system has been verified in comparison with alternative approaches

A basic production planning behaviour desired in an FMS is to support routing flexibility and operation lag times. In this context, the following features are considered: • routing flexibility: alternative paths can be followed through the system for a given process plan [1]; • separable setup: each operation is subjected to a setup; the setup period is split in the following two independent activities to be performed in parallel: (i) the setup depending on the previous processed operation on the machine (sequence-dependent setup); (ii) the setup depending on the previous operation in the job routing (sequence-independent setup) [2]. Routing flexibility leads to the problem of flexible (or multiprocessor) job-shop scheduling (FJS) which extends the classic problem of job-shop scheduling where no alternative machine is present for processing an operation [3]. The FJS problem concerns two sub-problems: (i) assignment of each operation to one of the alternative machines (assignment sub-problem); (ii) ordering of the operations on each assigned machine (sequencing sub-problem), with the aim of optimising an objective function.

This paper proposes an ant colony optimisation which represents a challenging approach to the scheduling of FMSs including alternative machine tools, setup and transportation times. A number of innovative skills are present in the paper. The first is an approach based on the disjunctive graph model and a LS algorithm. They are able to support job-shop scheduling with transportation and setup times and integrate them with the selection of alternative machine tools per operation. The second feature is the pheromone trail structure that is based on the aforementioned disjunctive graph model. Finally, two original components, the routing-precedence-based visibility function and the method to approximate non-delay schedules are introduced to improve the performance when compared with other systems. The system is very effective to solve the FMS scheduling with a high variety of parts and products which generally include a high number of sequence-dependent setup activities. Moreover, it is more able to tackle stagnation and to offer a real-time performance with respect to the compared GA-based system. The system is able to support a wide range of FMS layouts and material-handling systems, although the proposed application is related to the discrete material-handling device. Future work will be directed along two main directions: (i) allowing the system to support operation flexibility (FMS planning and scheduling integration); (ii) increasing computing speed for real-time response behaviour in dynamic scheduling applications.