ترکیبی مدل شبکه پتری و AI بر اساس جستجوی دوگانه اکتشافی برای تولید انعطاف پذیر سیستم -بخش 1. مدل سازی شبکه پتری و اکتشافی جستجو

This two-part paper presents modelling and scheduling approaches for flexible manufacturing systems (FMS) using Petri nets (PNs) and artificial intelligence (AI) based heuristic search methods. In part I, the description of FMS formulation that will be considered throughout the paper is presented. A new class of PNs, Buffer-nets, for defining FMS is proposed, which enhances the modelling techniques for manufacturing systems with features that are considered difficult to model. An input language for automatic synthesis of these nets is developed. A scheduling architecture, which integrates PN models and AI techniques, is proposed. Finally, the complexity issues of manufacturing systems are addressed.

An flexible manufacturing system (FMS) usually consists of several numerically controlled manufacturing machines, and automated material handling systems that transport work-pieces between machines and tool systems. In a facility with routing flexibility, each product can be manufactured via one of several available routes. A high-level control system must decide what resources are to be assigned to what product and at what time, so as to optimise some criteria, e.g. makespan, cost, etc. The purpose of scheduling is then to determine when to process which job by which resources so that production constraints are satisfied and production objectives are met. Many industry and research communities are now focusing on developing methods for quickly solving real-world scheduling problems—a challenge that maintains its momentum because no perfect solution has been found for all problems, due primarily to the complexity of FMS scheduling. The general FMS scheduling problem belongs to one of the NP hard combinatorial problems (Tzafestas & Triantafyllakis, 1993) for which the development of optimal polynomial algorithms is unlikely.

PN allows the systematic modelling of high abstractions of FMS. A new class of PN B-nets or Buffer-nets has been proposed and studied. A formal language for defining basic Job Shop Systems has been introduced and the semantics of this language have been presented. This paper has provided the modelling efforts upon which the further stages of the research will build. Based on the framework developed in this paper, several new scheduling algorithms have been developed in Part II. The basic structure of the combination of Petri net modelling and heuristic search methodologies has been presented in this paper. It has been shown that it is possible to obtain formalised heuristic information from the mathematical expression of a PN that can be integrated with the traditional search strategies. However, to make this integration useful, the complexity explosion for larger problems must be considered. This issue will be addressed in Part II.