Stability measure for a generalized assembly line balancing problem

Gurevsky, Evgeny; Battaïa, Olga; Dolgui, Alexandre

doi:10.1016/j.dam.2012.08.037

Cited by 47 publications

(15 citation statements)

References 30 publications

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“…Constraints (11) ensure that each task is allocated to exactly one workstation. As for constraints (12), they state that the load of any workstation does not exceed the cycle time.…”

Section: Milp Formulation For Pmentioning

confidence: 99%

“…Constraints (19) and (26) are same as (11) and 18, they provide that each task j is allocated to exactly one workstation from Q (j). Based on Property 1, constraints (20) and (21) state that the processing time deviation ξ j of any task j is set to ρ ∞ , which in turn is not greater than UB ∞ .…”

Section: Milp Formulation For P ∞mentioning

confidence: 99%

“…These positive outcomes have inspired several other studies. Thus, in [10], the results obtained for SALBP-1 and SALBP-2 were generalized for SALBP-E. A robust version for a more complex assembly line balancing problem subject to task time uncertainty has been also proposed in [11]. For that problem, the stability radius in the sense of feasibility was considered as the second objective to be maximized.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Maximizing the robustness for simple assembly lines with fixed cycle time and limited number of workstations

Rossi

Gurevsky

Battaïa

et al. 2016

Discrete Applied Mathematics

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“…Constraints (11) ensure that each task is allocated to exactly one workstation. As for constraints (12), they state that the load of any workstation does not exceed the cycle time.…”

Section: Milp Formulation For Pmentioning

confidence: 99%

Section: Milp Formulation For P ∞mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Maximizing the robustness for simple assembly lines with fixed cycle time and limited number of workstations

Rossi

Gurevsky

Battaïa

et al. 2016

Discrete Applied Mathematics

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“…To anticipate the possible changes in the input data, several researchers studied robust formulations of assembly line balancing problems (Xu and Xiao, 2009;Gurevsky et al, 2013b). Other studies were conducted to evaluate the stability of the obtained solutions under variations of task times (Gurevsky et al, 2012(Gurevsky et al, , 2013a. These results help to implement robust line balancing solutions and to keep the initial task assignment to some extent without modifications of the line.…”

Section: Rebalancing Versus Balancingmentioning

confidence: 99%

Re-balancing problem for assembly lines: new mathematical model and exact solution method

Makssoud

Battaïa

Dolgui

et al. 2015

Assembly Automation

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International audienceThe purpose of this study is to develop a new mathematical model and an exact solution method for an assembly line rebalancing problem. When an existing assembly line has to be adapted to a new production context, the line balancing, resources allocation and component management solutions have to be revised. The objective is to minimize the number of modifications to be done in the initial line in order to reduce the time and investment needed to meet new production requirements. The proposed model is evaluated via a computational experiment. The obtained results the efficacy of the proposed method

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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. Hazır and Dolgui (2013) recently presented two robust SALBP-2 models having interval uncertainty for operation times and solved them by a decomposition method and enhancement strategies.…”

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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Stability measure for a generalized assembly line balancing problem

Cited by 47 publications

References 30 publications

Maximizing the robustness for simple assembly lines with fixed cycle time and limited number of workstations

Maximizing the robustness for simple assembly lines with fixed cycle time and limited number of workstations

Re-balancing problem for assembly lines: new mathematical model and exact solution method

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

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