Journal Article10.1016/J.CIE.2020.106347
Mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem
213
TL;DR: The results show that the sequence-based MILP model is the most efficient one, and the proposed CP model is effective in finding good quality solutions for the both the small-sized and large-sized instances.
read more
About: This article is published in Computers & Industrial Engineering. The article was published on 01 Apr 2020. The article focuses on the topics: Constraint programming & Job shop scheduling.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Distributed Scheduling Problems in Intelligent Manufacturing Systems
TL;DR: The achievements and current research status in this field are analyzed, particularly swarm intelligence and evolutionary algorithms, which are used for managing distributed scheduling problems in manufacturing systems are discussed and future research directions are pointed out.
154
A discrete artificial bee colony algorithm for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
TL;DR: A machine position-based mathematical model and a discrete artificial bee colony algorithm (DABC) for the DHFSP-SDST to optimise the makespan and results and statistical analyses validate that the DABC outperforms the best performing algorithm in the literature.
97
Decomposition-Based Multi-Objective Optimization for Energy-Aware Distributed Hybrid Flow Shop Scheduling with Multiprocessor Tasks
TL;DR: A mixed inter linear programming model and a Novel MultiObjective Evolutionary Algorithm based on Decomposition (NMOEA/D) are presented and proposed to address the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks.
95
Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
TL;DR: In this article , three mixed-integer linear programming (MILP) models and a constraint programming (CP) model are formulated for distributed hybrid flow shop scheduling with sequence-dependent setup times (DHFSP-SDST).
92
Solving energy-efficient distributed job shop scheduling via multi-objective evolutionary algorithm with decomposition
TL;DR: A mathematical model is presented and an effective modified multi-objective evolutionary algorithm with decomposition (MMOEA/D) is proposed, which outperforms other algorithms in the energy-efficient distributed job shop scheduling problem.
92
References
Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems
TL;DR: 3 different optimization models for minimizing Makespan are discussed and it is demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.
An ant colony optimization algorithm for load balancing in parallel machines with sequence-dependent setup times
TL;DR: This study introduces the problem of minimizing average relative percentage of imbalance (ARPI) with sequence-dependent setup times in a parallel-machine environment and a mathematical model that minimizes ARPI is proposed.
A study of integer programming formulations for scheduling problems
TL;DR: The results show that Manners model is not only the best formulation for both job-shop and flow- shop problems, but is also the best for the permutation flow-shop problem.
Mathematical models and a hunting search algorithm for the no-wait flowshop scheduling with parallel machines
TL;DR: A novel hunting search metaheuristic algorithm (HSA) is proposed to solve large instances of the no-wait flowshop with parallel machines where the objective is to minimise makespan.
Exact algorithms for a scheduling problem with unrelated parallel machines and sequence and machine-dependent setup times
TL;DR: A branch-and-bound algorithm (B&B) is developed and a solution provided by the metaheuristic GRASP is used as an upper bound and a set of instances is proposed for this type of problem.