Flexible job shop scheduling using zero-suppressed binary decision diagrams

Abstract

A flexible job shop scheduling problem (FJSP) is a widely studied NP-hard combinatorial problem. Its goal is to optimise the production plans for simultaneously produced parts, where each part production consists of executing various operations. Each operation can be executed on several, or even all, available machines. A distinctive subproblem of FJSP is the identification of feasible solutions. A feasible solution is an allocation plan (i.e. assignment of a machine to a particular operation of a part to be produced) yielding an execution schedule satisfying the given resource constraints. FJSP is applied primarily in manufacturing systems, but it can be used to optimise Internet traffic, cloud computing, and other resource scheduling problems as well. So far, the exact methods for solving FJSP have not been considered attractive, since they seemed incapable of coping with real-size problems. This paper proposes a novel exact approach to solving FJSP which can find and count out all schedules of relatively large systems. The approach is successful due to the power of a special data structure called zero-suppressed binary decision diagrams to represent and manipulate the set of all feasible solutions efficiently. All the algorithms are implemented and tested by using our free Binary Decision Diagram package called Biddy.

Multi-objective optimization of production scheduling with evolutionary computation: A review

“…Table 1 presents production scheduling classifications made by Graham et al (1979), which have made the production scheduling classification in three fields: Shop environment, job characteristics and optimality criteria. Planning and scheduling in the production systems are based on mathematical and heuristic methods (Meolic & Brezocnik, 2018), which enable the proper distribution of limited production capacities according to the necessary production activities (Mirshekarian & Šormaz, 2016). Production activities must be carried out in such a way that the company optimizes its performance while achieving the set goals (Alghazi, 2017).…”

Simulation Study of a Flexible Manufacturing System Regarding Sustainability

“…The importance of the manufacturing flexibility impact does not relate exclusively to smaller production of a company with a specific job shop or flexible job shop production type [14,15], but we can trace the trend of manufacturing flexibility phenomena in other types of production. The impact of personalisation requires some flexibility for each production type, including mass production type.…”

Simulation framework for determining the order and size of the product batches in the flow shop: A case study

“…R. Meolic and Z. Brezočnik proposed a new approach to solving job shop scheduling problems with an emphasis on identifying feasible solutions. The new approach allows all schedules of relatively large systems to be found using the data structure, the zero-suppressed binary decision diagrams [12].…”