Sequencing mixed-model assembly lines with risk-averse stochastic mixed-integer programming

2021 ◽  
pp. 1-18
Author(s):  
Ge Guo ◽  
Sarah M. Ryan
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Mixed Model ◽  
Mixed Integer ◽  
Risk Averse ◽  
Assembly Lines ◽  
Mixed Model Assembly Lines ◽  
Stochastic Mixed Integer Programming ◽  
Mixed Model Assembly

scholarly journals A Multiobjective Optimization Algorithm to Solve the Part Feeding Problem in Mixed-Model Assembly Lines

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Masood Fathi ◽  
Maria Jesus Alvarez ◽  
Farhad Hassani Mehraban ◽  
Victoria Rodríguez
Keyword(s):  
Mathematical Model ◽  
Mixed Model ◽  
Performance Measure ◽  
Mixed Integer ◽  
Computational Time ◽  
Assembly Lines ◽  
Mixed Model Assembly Lines ◽  
The Mathematical Model ◽  
Mixed Model Assembly ◽  
Part Feeding

Different aspects of assembly line optimization have been extensively studied. Part feeding at assembly lines, however, is quite an undeveloped area of research. This study focuses on the optimization of part feeding at mixed-model assembly lines with respect to the Just-In-Time principle motivated by a real situation encountered at one of the major automobile assembly plants in Spain. The study presents a mixed integer linear programming model and a novel simulated annealing algorithm-based heuristic to pave the way for the minimization of the number of tours as well as inventory level. In order to evaluate the performance of the algorithm proposed and validate the mathematical model, a set of generated test problems and two real-life instances are solved. The solutions found by both the mathematical model and proposed algorithm are compared in terms of minimizing the number of tours and inventory levels, as well as a performance measure called workload variation. The results show that although the exact mathematical model had computational difficulty solving the problems, the proposed algorithm provides good solutions in a short computational time.

Integrated Approach for Flexible Mixed Model Assembly Lines Balancing and Model Sequencing Problem

2014 ◽  
Vol 670-671 ◽  
pp. 1593-1600 ◽  
Author(s):  
Li Nie ◽  
Yue Wei Bai ◽  
Jun Wu ◽  
Chang Tao Pang
Keyword(s):  
Mixed Model ◽  
Optimal Solution ◽  
Integrated Approach ◽  
Mixed Integer ◽  
Assembly Lines ◽  
Sequencing Problem ◽  
Mixed Model Assembly Lines ◽  
Assembly Tasks ◽  
Mixed Model Assembly Line ◽  
Mixed Model Assembly

The manufacturers nowadays are forced to respond very quickly to changes in the market conditions. To adopt flexible mixed model assembly lines (MMAL) is a preferred way for manufacturers to improve competitiveness. Managing a mixed model assembly line involves two problems: assigning assembly tasks to stations (balancing problem) and determining the sequence of products at each station (sequencing problem). In order to solve both balancing and sequencing problem in MMAL simultaneously, an integrated mathematical model based on mixed integer programming (MIP) is developed to describe the problem. In the model, general type precedence relations and task duplications are considered. Due to the NP-hardness of the balancing and sequencing problem of MMAL, GA is designed to search the optimal solution. The efficiency of the GA is demonstrated by a case study.

scholarly journals An Analytical Framework for Handling Production Time Variety at Workstations of Mixed-model Assembly Lines

Procedia CIRP ◽  
2016 ◽  
Vol 41 ◽  
pp. 201-206 ◽  
Author(s):  
Stefan Keckl ◽  
Wolfgang Kern ◽  
Antoin Abou-Haydar ◽  
Engelbert Westkämper
Keyword(s):  
Mixed Model ◽  
Analytical Framework ◽  
Assembly Lines ◽  
Production Time ◽  
Mixed Model Assembly Lines ◽  
Mixed Model Assembly

A bi-level programming for transportation services procurement based on combinatorial auction with fuzzy random parameters

2018 ◽  
Vol 30 (5) ◽  
pp. 1162-1182 ◽  
Author(s):  
Fang Yan ◽  
Yanfang Ma ◽  
Cuiying Feng
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Traditional Approach ◽  
Algorithm Analysis ◽  
Mixed Integer ◽  
Content Type ◽  
Winner Determination ◽  
Stochastic Mixed Integer Programming ◽  
Maximum Utility ◽  
Algorithm Comparison

Purpose The purpose of this paper is to study a transportation service procurement bid construction problem from a less than a full truckload perspective. It seeks to establish stochastic mixed integer programming to allow for the proper bundle of loads to be chosen based on price, which could improve the likelihood that carrier can earn its maximum utility. Design/methodology/approach The authors proposes a bi-level programming that integrates the bid selection and winner determination and a discrete particle swarm optimization (PSO) solution algorithm is then developed, and a numerical simulation is used to make model and algorithm analysis. Findings The algorithm comparison shows that although GA could find a little more Pareto solutions than PSO, it takes a longer time and the quality of these solutions is not dominant. The model analysis shows that compared with traditional approach, our model could promote the likelihood of winning bids and the decision effectiveness of the whole system because it considers the reaction of the shipper. Originality/value The highlights of this paper are considering the likelihood of winning the business and describing the conflicting and cooperative relationship between the carrier and the shipper by using a stochastic mixed integer programming, which has been rarely examined in previous research.

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