Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system

Ghosh, Tamal; Doloi, B.; Dan, Pranab K.

doi:10.1007/s00170-015-8070-6

Cited by 11 publications

(4 citation statements)

References 44 publications

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“…To improve grouping efficacy of a cell formation problem, Zeb et al [64] presented the hybridization of SA with GA to combine exploration power of GA with the intensification power of SA. Ghosh et al [21] proposed a Quadratic Assignment Problem (QAP) model of the inter-cell layout design problem in a dynamic environment considering the material handling cost and a modified cells proximity relationship. Due to the NP-hard nature of the problem, they developed an improved GA and a SA algorithm.…”

Section: Cms Studies With a Sa Solution Approachmentioning

confidence: 99%

“…SA has been applied in numerous optimization problems in a considerable diversity of areas, including DCMS [8,12,17,21,24,26,28,29,33,37,39,42,51,56,64]. In this section, the elements of the extended SA are described as follows.…”

Section: Simulated Annealing Algorithmmentioning

confidence: 99%

“…However, SA has found a special place in CMS studies due to its strength in handling complex problems, especially with numerous constraints that are common in CMS models. Therefore, many studies have recently employed SA as an efficient solution approach and reported satisfactory results [8,12,17,21,24,33,51,56,64] The main contribution of this paper, regarding the reviewed articles and unveiled necessities of integrating the discussed decisions including CF, scheduling, TP and PP is presenting a comprehensive model for designing a DCMS into an SC integrating (1) CF under a dynamic environment, (2) MRP with one-level BOM, (3) parts scheduling, (4) GFCTP and (5) PP strategies for satisfying multi-markets demands. The integrated model simultaneously incorporates several important design features including multi-markets with different parts demands and due dates, heterogeneous vehicles with different speed and fixed charges, raw materials with different lead times and usage coefficient, cell size limits, machines capacity, material handling time, operation time, alternative processing routes, employing inventory holding and backorder strategies for fulfilling markets demands, keeping inventories of raw materials in the plant warehouse, cell reconfiguration, intra/inter-cellular movement and operations sequence to bring the model closer to manufacturing realities.…”

Section: Introductionmentioning

confidence: 99%

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Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system

et al. 2021

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In this paper, to integrate the decisions of parts scheduling, Material Requirement Planning (MRP), Production Planning (PP) and Transportation Planning (TP) for designing a Cellular Manufacturing System (CMS) under a dynamic environment, a Mixed-Integer Nonlinear Programming (MINLP) mathematical model is formulated. The proposed mathematical model integrates extensive coverage of significant manufacturing characteristics in designing a CMS to be implemented in a three-layer supply chain. The considered features include markets demands, heterogeneous vehicles, raw materials requirements planning, parts due dates, cell size limits, machines capacity, intra/inter cell material handling time/cost, transportation time/cost, operation time, alternative processing routes in addition to the main decisions of parts scheduling, PP, TP and dynamic cell formation. Also, some novel characteristics are incorporated based on a three-layer supply chain that make the presented model remarkable respect to the literature including 1) In the first layer, planning the orders of raw materials with different lead times and usage coefficients is performed, 2) In the second layer, decisions of dynamic cell formation and parts scheduling are made, and 3) In the third layer, optimal vehicles are selected as a generalized fixed-charge TP based on transportation time and cost to satisfy multi-markets with different demand volumes. The components in the objective function to be minimized include total costs of holding the parts inventories in the markets, backorders, tardiness, transportation of the parts from the plant to the markets, purchase of raw materials, keeping raw materials in the plant warehouse, intercellular/intracellular movements and machine relocation. An illustrative numerical example is solved by the CPLEX solver to illustrate the achievements obtained by the incorporated characteristics in the integrated model. Furthermore, a sensitivity analysis is performed to assess the effects of important parameters on the model performance. Since the proposed model is NP-hard, a Simulated Annealing (SA) algorithm is improved by an elaborately-designed matrix-based chromosome representation is applied to represent all decision variables, as well as a sequential procedure generating initial solutions. Several test problems either generated randomly or taken from the literature with various sizes are solved and the results are compared with the solutions gained using CPLEX solver. The comparisons results show that the designed SA is capable of evolving optimal or near-optimal solutions with reasonable relative gaps in a computationally satisfactory manner.

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Section: Cms Studies With a Sa Solution Approachmentioning

confidence: 99%

Section: Simulated Annealing Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system

et al. 2021

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“…Jiying et al [31] used an artificial bee colony algorithm (ABC) for resolving a mathematical model to find the feasible solution considering human factors like safety, rich efficiency, low price and sustainability with penalty function. Ghosh et al [32] developed a soft computing technique by using improved GA and a SA heuristic (SAH) to solve dynamic multi-objective layout problems. Turanoglu and Akkaya [33] proposed fuzzy decision support system by integrating multiple input types for determining the closeness rates between the departments in the DFLP.…”

Section: Metaheuristicsmentioning

confidence: 99%

A Research on Dynamic Facility Layout Problems

Balachandar G*,

Reddy C

2020

IJRTE

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Among the several features of the manufacturing system, the facility layout problem (FLP) is a one of the significant issues. An endeavour is made in this paper to show the best review on Dynamic Facility Layout Problems (DFLPs). Here, a writing survey is made by referring to various papers on DFLPs. This paper aims to discuss present and future trends in DFLP research based on past research data such as layout evolution, characteristics of the workshop, problem formulation and Resolution approaches.

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A Systematic Literature Review of Facility Layout Problems and Resilience Factors in the Industry

Flores-Siguenza

Siguenza-Guzmán

Lema

et al. 2022

Communications in Computer and Information Science

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Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system

Cited by 11 publications

References 44 publications

Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system

Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system

A Research on Dynamic Facility Layout Problems

A Systematic Literature Review of Facility Layout Problems and Resilience Factors in the Industry

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