Balancing of simple assembly lines under variations of task processing times

Gurevsky, Evgeny; Battaïa, Olga; Dolgui, Alexandre

doi:10.1007/s10479-012-1203-5

Cited by 66 publications

(20 citation statements)

References 27 publications

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“…Other authors have also tackled some variants of combinatorial optimization problems: stability aspects of the solutions for the traveling salesman problem when the k ‐best solution procedure is applied (cf., Libura et al., ); the sensitivity analysis of the solutions for scheduling problems (cf., Hall and Posner, ); the so‐called balancing of simple assembly where the stability of approximate and optimal solutions, under variations of the processing time of some tasks, has been tackled in Gurevsky et al. (), searching for the stability of the solutions for the minimum spanning tree (cf., Pettie, ); and the lot‐sizing problem (cf., van Hoesel and Wagelmans, ). Other studies on sensitivity and stability analyses can be found in Emelichev and Podkopaev (), Libura (), and Woeginger ().…”

Section: Related Workmentioning

confidence: 99%

Sensitivity analysis of the setup knapsack problem to perturbation of arbitrary profits or weights

Al-Maliky

Hifi

Mhalla

2017

Int Trans Operational Res

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The setup knapsack problem can be viewed as a more complex version of the well‐known classical knapsack problem. An instance of such a problem may be defined by a set scriptN of n items that is divided into m different classes Fi,1≤i≤m. For each class, only one item is considered as a setup item. The aim of the problem is to pack a subset of items in a knapsack of a predefined capacity that maximizes an objective function. In this paper, we analyze the sensitivity of an optimal solution depending on the variation of the profits or weights of arbitrary items. The optimality of the solution at hand is guaranteed by establishing the sensitivity interval that is characterized by both lower and upper values (called limits). First, two cases are distinguished when varying the profits: perturbation of the profit of an item (either ordinary or setup item) and, variation of the profits of a couple of items containing both setup and ordinary items belonging to the same class. Second, two cases are studied, where the perturbation concerns the weights: the variation is relied on the weight of an item and, the case of the variation of the weights of a subset of items. The established results are first illustrated throughout a didactic example, where both approximate and exact methods are used for analyzing the quality of the proposed results. Finally, an extended experimental part is proposed in order to evaluate the effectiveness of the proposed limits.

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Section: Related Workmentioning

confidence: 99%

Sensitivity analysis of the setup knapsack problem to perturbation of arbitrary profits or weights

Al-Maliky

Hifi

Mhalla

2017

Int Trans Operational Res

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“…For instance, Gurevsky et al (2012) dealt with the SALBP-E when having task times within intervals and proposed a way to find a compromise between the objective function minimization and a stability ratio (a parameter to reflect the risk aversion coefficient of a decision maker and the conservatism). A related stability study was done in Gurevsky et al (2013) but for the case of an ALB problem where a workstation can have several workplaces, there are exclusion constraints, and the processing times of the tasks can vary during the line life cycle.…”

Section: Robust Optimization For Assembly Line Balancingmentioning

confidence: 99%

A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand

Chica

Bautista

Cordón

et al. 2016

Omega

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Changes in demand when manufacturing different products require an optimization model that includes robustness in its definition and methods to deal with it. In this work we propose the r-TSALBP, a multiobjective model for assembly line balancing to search for the most robust line configurations when demand changes. The robust model definition considers a set of demand scenarios and presents temporal and spatial overloads of the stations in the assembly line of the products to be assembled. We present two multiobjective evolutionary algorithms to deal with one of the r-TSALBP variants. The first algorithm uses an additional objective to evaluate the robustness of the solutions. The second algorithm employs a novel adaptive method to evolve separate populations of robust and non-robust solutions during the search. Results show the improvements of using robustness information during the search and the outstanding behavior of the adaptive evolutionary algorithm for solving the problem. Finally, we analyze the managerial impacts of considering the r-TSALBP model for the different organization departments by exploiting the values of the robustness metrics.

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“…In some environments, however, the time duration of all or some of the tasks may change during the life cycle of the line due to instability of operators pace, motivation, changes in product and station characteristics, etc. The effect of such phenomena on the line balance, and some analytical properties on the stability of the line were given in Sotskov et al (2006), Gurevsky et al (2012), Sotskov et al (2012) and others.…”

Section: Literature Reviewmentioning

confidence: 99%

The effect of buffers and work sharing on makespan improvement of small batches in assembly lines under learning effects

Bukchin

Wexler

2015

IIE Transactions

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The effect of workers" learning curve on production rate in manual assembly lines is significant when producing relatively small batches of different products. This research studies this effect and suggests applying work-sharing mechanism among the workers to improve the makespan (time to complete the batch). The proposed mechanism suggests that adjacent crosstrained workers will help each other in order to reduce idle times caused by blockage and starvation. The effect of work-sharing and buffers on the makespan is studied and compared with a baseline situation, where the line does not contain any buffers and work-sharing is not applied. Several linear-programming (LP) and mixed-integer linear-programming (MILP) formulationsfor makespan minimization are presented. These formulations provide optimal work-allocation to stations and optimal parameters of the work-sharing mechanism. 1 Corresponding author: bukchin@tau.ac.il Downloaded by [University of Nebraska, Lincoln] at 01:42 11 October 2015 2A numerical study is conducted to examine the effect of buffers and work-sharing on the makespan reduction in different environment setting. Numerical results are given along with some recommendations regarding the system design and operation.

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Balancing of simple assembly lines under variations of task processing times

Cited by 66 publications

References 27 publications

Sensitivity analysis of the setup knapsack problem to perturbation of arbitrary profits or weights

Sensitivity analysis of the setup knapsack problem to perturbation of arbitrary profits or weights

A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand

The effect of buffers and work sharing on makespan improvement of small batches in assembly lines under learning effects

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