An improved multiverse optimization (IMVO) algorithm is proposed herein for the fuzzy flexible job-shop scheduling problem pertaining to non-deterministic polynomial-time hard (NP-hard) problem. First, we designed a hybrid initialization method improve quality of initial solution, and thereafter, introduced self-crossing technique along with an insert-based heuristic simulate process exchanging...

Abstract Quantum Annealing (QA) is a metaheuristic for solving optimization problems in time-efficient manner. Therefore, quantum mechanical effects are used to compute and evaluate many possible solutions of an problem simultaneously. Recent studies have shown the potential QA such complex assignment within milliseconds. This also applies field job shop scheduling, where existing approaches ho...

The nature of construction and formulation the multi-objective functions in flexible job shop (FJS) provides great insights about study technique mechanism scheduling helping to prioritize efforts for optimizing manufacturing execution performance, which draw focus researchers at home abroad. From perspective model, solution method objective function, this paper reviews analyzes related academi...

As a typical transportation tool in the intelligent manufacturing system, Automatic Guided Vehicle (AGV) plays an indispensable role automatic production process of workshop. Therefore, integrating AGV resources into scheduling has become research hotspot. For problem flexible job shop adopting segmented AGV, dual-resource optimization mathematical model machine tools and AGVs is established by...

— Flexible Job Shop scheduling problem (FJSSP) is an important scheduling problem which has received considerable importance in the manufacturing domain. In this paper a genetic algorithm (GA) based scheduler is presented for flexible job shop problem to minimise makespan. The proposed approach implements a domain independent GA to solve this important class of problem. The scheduler is impleme...

The problem of efficiently scheduling production jobs on several machines is an important consideration when attempting to make effective use of a multimachines system such as a flexible job shop scheduling production system (FJSP). In most of its practical formulations, the FJSP is known to be NP-hard [8][9], so exact solution methods are unfeasible for most problem instances and heuristic app...

In this paper, we introduce a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO) algorithm, consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO algorithm is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). Flexible job-shop scheduling is very important in...