A meta-heuristic to solve the just-in-time job-shop scheduling problem

A Relax-and-Solve Algorithm for the Ordered Flow-Shop Scheduling Problem

“…In this section we propose an efficient relax-andsolve (R&S) heuristic algorithm for the ordered flow-shop scheduling problem. The R&S algorithm was designed by [9,10,11,12]. Given an initial sequence, the R&S algorithm obtains an improved solution through iterative relaxation of a subset (of the given sequence) of operations, and solving the subset, i.e., re-ordering and re-scheduling by using optimization techniques.…”

Tailoring Job Shop Scheduling Problem Instances Through Unified Particle Swarm Optimization

“…Similarly, Wu et al researched several approaches for when external factors change processing times, such as breakdowns and other failures [9]. One may also find the just-in-time variant, where operations within jobs have due dates and where completing an operation either early or late leads to a penalty [10]. Some other examples include the works of [11]- [14].…”

“…Due to the exploratory nature of this stage, and to keep things as simple as possible, we only considered the LPT and SPT heuristics. Furthermore, we tailored 30 instances enhancing each heuristic, i.e., following Equation (10). This brought about a total of 60 instances distributed across both sets.…”

An Improved Integrated Scheduling Algorithm with Process Sequence Time‐Selective Strategy

“…Effective scheduling optimization algorithm can maximize the production efficiency on the premise of satisfying the constraints of enterprise orders, equipment, and other hardware and software resources. At present, scholars have done a lot of research on the workshop scheduling problem, and most scheduling problems are mainly divided into job shop [1][2][3][4][5][6][7][8][9][10] and flow shop [11][12][13][14][15][16][17][18][19].…”