scholarly journals A Multi-objective Mathematical Model Considering Economic and Social Criteria in Dynamic Cell Formation

2014 ◽  
pp. 46-53 ◽  
Author(s):  
Farzad Niakan ◽  
Armand Baboli ◽  
Thierry Moyaux ◽  
Valerie Botta-Genoulaz
Keyword(s):  
Mathematical Model ◽  
Cell Formation ◽  
Multi Objective ◽  
Dynamic Cell

scholarly journals A new multi-objective mathematical model for dynamic cell formation under demand and cost uncertainty considering social criteria

2016 ◽  
Vol 40 (4) ◽  
pp. 2674-2691 ◽  
Author(s):  
Farzad Niakan ◽  
Armand Baboli ◽  
Thierry Moyaux ◽  
Valérie Botta-Genoulaz
Keyword(s):  
Mathematical Model ◽  
Cell Formation ◽  
Cost Uncertainty ◽  
Multi Objective ◽  
Dynamic Cell

scholarly journals Integrated Dynamic Cell Formation-Production Planning: A New Mathematical Model

2017 ◽  
Vol 24 (5) ◽  
pp. 2550-2566 ◽  
Author(s):  
Masoud Rabbani ◽  
Sina Keyhanian ◽  
Neda Manavizadeh ◽  
Hamed Farrokhi-Asl
Keyword(s):  
Mathematical Model ◽  
Production Planning ◽  
Cell Formation ◽  
Dynamic Cell

A nonlinear multi-objective model of dynamic cell formation

2008 ◽  
Author(s):  
Wang Xiaoqing ◽  
Tang Jiafu ◽  
Gong Jun ◽  
Chen Mei
Keyword(s):  
Cell Formation ◽  
Multi Objective ◽  
Dynamic Cell ◽  
Objective Model

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

2020 ◽  
Author(s):  
Shima Shafiee-Gol ◽  
reza kia ◽  
Reza Tavakkoli-Moghaddam ◽  
Mohammad Kazemi ◽  
Mehdi A. Kamran
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Production Planning ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Raw Materials ◽  
Cell Formation ◽  
Time Cost ◽  
Cellular Manufacturing System ◽  
Dynamic Cell

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.

Integrated dynamic cell formation with operator assignment and inter-cell layout problems: A mathematical model

2015 ◽  
Vol 231 (9) ◽  
pp. 1658-1669 ◽  
Author(s):  
Saeed Sadeghi ◽  
Mohammad Ali Forghani ◽  
Masoud Seidi
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Cellular Manufacturing System ◽  
Numerical Examples ◽  
Proposed Model ◽  
Dynamic Cell ◽  
Operator Assignment

Designing a cellular manufacturing system involves four major decisions: cell formation, cellular layout, operator assignment and cellular scheduling which should be considered, simultaneously. This article presents a new mathematical model to solve the cell formation, operator assignment and inter-cell layout problems, concurrently. The objectives of proposed model are minimization of inter–intra cell part movements, machine relocation cost and operator-related issues including hiring, firing, training and salary costs. Two numerical examples in both small and large sizes are optimally solved by the Lingo software to verify and validate the proposed mathematical model. Also, a sensitivity analysis is performed to analyze the behavior of operators in different production periods.

Sign in / Sign up

Export Citation Format

Share Document