The third comprehensive survey on scheduling problems with setup times/costs

Minimizing the total completion time in a single-machine scheduling problem with a time-dependent learning effect

An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem

Distributed permutation flowshop scheduling problem (DPFSP) has become a very active research area in recent years. However, minimizing total flowtime in DPFSP, a very relevant and meaningful objective for today's dynamic manufacturing environment, has not captured much attention so far. In this paper, we address the DPFSP with total flowtime criterion. To suit the needs of different CPU time demands and solution quality, we present three constructive heuristics and four metaheuristics. The constructive heuristics are based on the well-known LR and NEH heuristics. The metaheuristics are based on the high-performing frameworks of discrete artificial bee colony, scatter search, iterated local search, and iterated greedy, which have been applied with great success to closely related scheduling problems. We explore the problem-specific knowledge and accelerations to evaluate neighboring solutions for the considered problem. We introduce advanced and effective technologies like a referenced local search, a strategy to escape from local optima, and an enhanced intensive search method for the presented metaheuristics. A comprehensive computational campaign against the closely related and well performing algorithms in the literature is carried out. The results show that both the presented constructive heuristics and metaheuristics are very effective for solving the DPFSP with total flowtime criterion.

Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem

Some scheduling problems with general position-dependent and time-dependent learning effects

http://ira.lib.polyu.edu.hk/bitstream/10397/1307/1/Single-machine-time-dependent-Learning_1.pdf

Single-machine scheduling with a time-dependent learning effect

Single-machine scheduling with past-sequence-dependent setup times and time-dependent learning effect

Single-machine due-window assignment problem with learning effect and deteriorating jobs

https://ira.lib.polyu.edu.hk/bitstream/10397/1266/1/new-w_jC_j-sp-digraphs-deterioration-new.pdf

Ji-Bo Wang

Papers

Single-machine scheduling with a time-dependent learning effect

Single-machine scheduling with past-sequence-dependent setup times and time-dependent learning effect

Single-machine due-window assignment problem with learning effect and deteriorating jobs

Single-machine scheduling with deteriorating jobs under a series-parallel graph constraint

Minimizing total completion time in a two-machine flow shop with deteriorating jobs