Scheduling hybrid flowshops with sequence dependent setup times to minimize makespan and maximum tardiness

Taghizadeh

Int J Syst Assur Eng Manag

et al. 2014

In the retailer-supplier partnerships, the vendormanaged inventory (VMI) is one of the important policies in the supply chain management (SCM) to reduce the bullwhip effect. As there is a lack of study on the central warehouse via delivering cost in VMI literature, this paper presents a VMI model in SCM including single-vendor, multi-retailer, and single-warehouse. While the vendor confronts with two constraints, namely the number of orders and budget, the purpose of this research is to find order size, the shortest possible route, and replenishment frequencies for the vendor and the retailers to minimize the total inventory cost. As the proposed model is an NP-hard problem, a meta-heuristics namely particle swarm optimization (PSO) is employed to optimize the proposed model. Since there is no available benchmark for evaluation of the proposed method, a genetic algorithm is used to validate and verify the solution presented by PSO. Moreover, Taguchi method in the design of experiments calibrates the parameters of the algorithm to provide the reliable solution. Finally, the conclusion and further studies are presented.

Section: Comparison Of Solution Algorithmsmentioning

confidence: 99%

Optimizing a vendor managed inventory (VMI) model considering delivering cost in a three-echelon supply chain using two tuned-parameter meta-heuristics

Taghizadeh

Int J Syst Assur Eng Manag

et al. 2014

Journal of the Operational Research Society

“…In Table 2, we based the number of jobs in our experiments on previous flowshop scheduling research by Naderi et al (2009). Following from the classical problem introduced by Taillard (1990) and revisited by Ruiz et al (2005) we used uniformly distributed processing times in the experiments.…”

Section: Experimental Designmentioning

confidence: 99%

Minimizing energy consumption and makespan in a two-machine flowshop scheduling problem

Mansouri

Aktaş

2016

Energy consumption has become a key concern for manufacturing sector because of negative environmental impact of operations. We develop constructive heuristics and multi-objective genetic algorithms (MOGA) for a two-machine sequence-dependent permutation flowshop problem to address the trade-off between energy consumption as a measure of sustainability and makespan as a measure of service level. We leverage the variable speed of operations to develop energy-efficient schedules that minimize total energy consumption and makespan. As minimization of energy consumption and minimization of makespan are conflicting objectives, the solutions to this problem constitute a Pareto frontier. We compare the performance of constructive heuristics and MOGAs with CPLEX and random search in a wide range of problem instances. The results show that MOGAs hybridized with constructive heuristics outperform regular MOGA and heuristics alone in terms of quality and cardinality of Pareto frontier. We provide production planners with new and scalable solution techniques that will enable them to make informed decisions considering energy consumption together with service objectives in shop floor scheduling.

“…When there is any machine fault, the original scheduling scheme may no longer be the optimal one and needs to be redesigned, which means, re-scheduling strategy needs to be used to address the uncertainties in flow shop scheduling brought by product blockage and machine faults [21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Scheduling Optimization Model Considering Product Blockage and Machine Faults

Yin¹,

Liu²,

Yeh³

2017

Int. j. simul. model.

Considering problems like product blockage and machine faults in the batch scheduling of product assembly lines, this paper proposes a multi-objective flow shop batch scheduling model taking these problems into account, and by comparing with the traditional flow shop scheduling model, it verifies the feasibility and superiority of this model. The results show that, regarding the product blockage problem, this paper improves the MWH heuristic algorithm, leading to better quality of the initial population produced; and that it also proposes a new ISBOX crossover operator algorithm, which is used in combination with the nondominated solution information to calculate the new solution for offsprings, improving the local search capability of the algorithm. In order to address machine faults, this paper obtains new solutions by optimizing the maximum completion time and the early completion time, takes the new solutions as the initial population, and uses the proposed model to optimize the robustness and stability of the existing algorithm. By comparing the proposed model and the traditional scheduling model in terms of product blockage and machine fault, this paper finds that the proposed algorithm has high local and global convergence, and generates high-quality nondominated solutions. According to the re-scheduling strategy, this algorithm can effectively reduce the effects of product blockage and machine faults on the objective function.