An Improved African Vulture Optimization Algorithm for Dual-Resource Constrained Multi-Objective Flexible Job Shop Scheduling Problems

Abstract

According to the characteristics of flexible job shop scheduling problems, a dual-resource constrained flexible job shop scheduling problem (DRCFJSP) model with machine and worker constraints is constructed such that the makespan and total delay are minimized. An improved African vulture optimization algorithm (IAVOA) is developed to solve the presented problem. A three-segment representation is proposed to code the problem, including the operation sequence, machine allocation, and worker selection. In addition, the African vulture optimization algorithm (AVOA) is improved in three aspects: First, in order to enhance the quality of the initial population, three types of rules are employed in population initialization. Second, a memory bank is constructed to retain the optimal individuals in each iteration to increase the calculation precision. Finally, a neighborhood search operation is designed for individuals with certain conditions such that the makespan and total delay are further optimized. The simulation results indicate that the qualities of the solutions obtained by the developed approach are superior to those of the existing approaches.

Flexible Job Shop Scheduling Method for Optimizing Mold Resource Setup Time

“…Constraints in the flexible multi-resource job shop scheduling problem typically focus on various resources. For example, He et al [15] explored a dual-resource-constrained flexible job shop scheduling problem, which involved machine and worker constraints. They introduced an improved African vulture optimization algorithm to address this issue, utilizing the AVOA algorithm based on position updating formulas and position vectors.…”

A Strengthened Dominance Relation NSGA-III Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

“…FT datasets come in different sizes, including 6 × 6, 10 × 10, and 20 × 5. FT06 has processing time in the range [1,10], and FT10 and FT20 have processing time in the range [1,99]. The ABZ dataset is of size 20 × 15, with processing time in the range [10,40].…”

“…SWV dataset includes three different sizes: 20 × 10, 20 × 15, and 50 × 10. The processing time falls within the range [1,100]. LA dataset consists of six different sizes: 10 × 5, 15 × 5, 20 × 5, 15 × 10, 20 × 10, and 30 × 10.…”

“…The Job Shop Scheduling Problem (JSSP) refers to a class of problems where the objective is to optimize scheduling by arranging the processing sequence of operations within a set of tasks, while adhering to task-specific constraints and precedence relations among operations [1]. Job shop scheduling, as a critical component of the intelligent manufacturing industry, plays a vital role in resolving the conflicts between shop floor production and optimization objectives [2].…”

Performance Optimization for a Class of Petri Nets

“…Performance optimization in flexible manufacturing systems has received great attention in recent decades [ 1 ]. Such automated systems with synchronization, concurrency, and time delay can usually be modeled by timed marked graphs (TMGs), an important subclass of PNs that are proven to be useful in modeling manufacturing systems, queue systems, and railway transportation systems [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ].…”