Coordinative production and maintenance scheduling problem with flexible maintenance time intervals

Abstract

This study investigates the simultaneous scheduling of production and planning of maintenance activities in the flow shop scheduling environment. The problem is considered in a bi-objective form, minimizing the makespan as the production scheduling criterion and minimizing the system unavailability as the maintenance planning criterion. We propose the coordinative production and maintenance scheduling model in which the time interval between consecutive maintenance activities as well as the number of maintenance activities on each machine are assumed to be non-fixed. The coordinative model aims to find the best permutation of jobs as the production problem and to assign the maintenance activities into the schedule as the maintenance problem, simultaneously. Moreover, a special setting called single server maintenance is introduced and discussed. A biobjective ant colony system algorithm is presented to solve the problem in focus, introducing some novel ideas. CDS and NEH heuristics are applied to define the heuristic information part of the proposed algorithm. Some experiments are carried out to select the appropriate heuristic method between CDS and NEH. Moreover, some experiments are performed using the well-known Taillard benchmark, comparing the performance of the proposed algorithm with another ant colony optimization algorithm. Computational experiments indicate the effectiveness of the proposed algorithm.

Energy-aware flexible job shop scheduling problem and preventive maintenance under the limited resource constraints

“…In this study, we consider a total flexible job shop scheduling environment, so all machines can process every operation. Concerning the maintenance aspect, preventive maintenance is executed as a strategy to decrease the probability of the potential failure of the system before they happen and as a result, it increases the availability of the production system (Khatami & Zegordi, 2017). In this work, a new approach is proposed to cope with two distinct, yet dependent decisions simultaneously: production scheduling decisions, as well as PM decisions.…”

An Operational Safety Evaluation Method for Manned Transport Aircraft and Large UAV in Mixed Airspace

“…Secondly, the airport has a wide range of local airspace. If ground equipment is used for trajectory observation and prediction [44], the increase of observation distance will lead to the increase of evaluation error [45]. erefore, the design of PTD-MI algorithm needs to consider the optimization of evaluation error.…”

Makespan minimization for the m-machine ordered flow shop scheduling problem

“…Therefore, a total number of 120 instances were produced. For more recent studies of Taillard's instances we refer the interested reader to Khatami and Zegordi (2017); Khorasanian and Moslehi (2017) and Liu et al (2017). Vallada et al (2015) carried out extensive experiments and selected 240 "small" instances and 240 "large" instances, from a pool of 72,000 instances.…”