Application of Hybrid Genetic Algorithm for CLSC Network Design Problem in Fashion Footwear Industry—A Case Study Approach (original) (raw)
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The implementation of closed loop supply chain system is becoming essential for fashion leather products industry to ensure an economically sustainable business model and eco-friendly industrial practice as demanded by the environmental regulations, consumer awareness and the prevailing social consciousness. In this context, this research work addresses a closed loop supply chain network problem of fashion leather goods industry, with an objective of minimizing the total cost of the entire supply chain and also reducing the total waste from the end of life product returns. The research work commenced with a literature review on the reverse and closed loop supply chain network design problems of fashion and leather goods industry dealt in the past.
ABSTRACT This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems. KEYWORDS Closed Loop Supply Chain, Genetic Algorithms, HGA, Meta-Heuristics, MINLP, Model, Network Design, Optimization
Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach
Mathematics, 2020
In this paper, we propose a solution to the sustainable closed-loop supply chain (SCLSC) design problem. Three factors (economic, environmental, and social) are considered for the problem and the three following requirements are addressed while satisfying associated constraint conditions: (i) minimizing the total cost; (ii) minimizing the total amount of CO2 emission during production and transportation of products; (iii) maximizing the social influence. Further, to ensure the efficient distribution of products through the SCLSC network, three types of distribution channels (normal delivery, direct delivery, and direct shipment) are considered, enabling a reformulation of the problem as a multi-objective optimization problem that can be solved using Pareto optimal solutions. A mathematical formulation is proposed for the problem, and it is solved using a hybrid genetic algorithm (pro-HGA) approach. The performance of the pro-HGA approach is compared with those of other conventional ...
Literature Review on Network Design Problems in Closed Loop and Reverse Supply Chains
The productivity of an organization is very much affected by non-value adding activity like logistics, which moves the resources from suppliers to factory, raw materials/semi-finished items within the factory and finished goods from factory to customers via a designated distribution channel called as forward logistics. In some cases, parts of the products such as automobiles, computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery strategy through reverse logistics network which is integrated in a sustainable closed loop supply chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics network. This paper gives a comprehensive review of literature of the design of networks for the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions of the researchers are classified into nine categories based on the methods used to design the logistics network.
A steady-state genetic algorithm for multi-product supply chain network design
Computers & Industrial Engineering, 2009
Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management (SCM). The problem is often an important and strategic operations management problem in SCM. The design task involves the choice of facilities (plants and distribution centers (DCs)) to be opened and the distribution network design to satisfy the customer demand with minimum cost. This paper presents a solution procedure based on steady-state genetic algorithms (ssGA) with a new encoding structure for the design of a single-source, multi-product, multi-stage SCN. The effectiveness of the ssGA has been investigated by comparing its results with those obtained by CPLEX, Lagrangean heuristic, hyrid GA and simulated annealing on a set of SCN design problems with different sizes.
2019
In the current world, the debate on the reinstatement and reuse of consumer products has become particularly important. Since the supply chain of the closed loop is not only a forward flow but also a reverse one; therefore, companies creating integrity between direct and reverse supply chain are successful. The purpose of this study is to develop a new mathematical model for closed loop supply chain network. In the real world the demand and the maximum capacity offered by the supplier are uncertain which in this model; the fuzzy theory discussion was used to cover the uncertainty of the mentioned variables. The objective functions of the model include minimizing costs, increasing revenues of recycling products, increasing cost saving from recycling and environmental impacts. According to the NP-hard, an efficient algorithm was suggested based on the genetic Meta heuristic algorithm to solve it. Twelve numerical problems were defined and solved using the NSGA-II algorithm to validate...
Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm
International Journal of Information Systems and Supply Chain Management, 2018
This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illus...
In this study, a multi level reverse logistics network is developed for a single product. Reverse logistics is a logistic activity beginning from intake of products returned by customers to selling of remanufactured or new products in market; so, it is considered that reverse flow of used products is from various sources like customers, dealers, retailers, manufacturers, etc., to remanufacturer and followed by transportation to secondary market. Due to uncertainties, any traditional supply chain approach to identify potential manufacturing facilities in this situation cannot be employed. Hence, Genetic Algorithm (GA) is used for optimization and minimization of various costs involved in reverse logistics process. A sample numerical data is considered to test performance of the proposed model.
Research Journal of Applied Sciences, Engineering and Technology, 2014
In this study, a multi level reverse logistics network is developed for a single product. Reverse logistics is a logistic activity beginning from intake of products returned by customers to selling of remanufactured or new products in market; so, it is considered that reverse flow of used products is from various sources like customers, dealers, retailers, manufacturers, etc., to remanufacturer and followed by transportation to secondary market. Due to uncertainties, any traditional supply chain approach to identify potential manufacturing facilities in this situation cannot be employed. Hence, Genetic Algorithm (GA) is used for optimization and minimization of various costs involved in reverse logistics process. A sample numerical data is considered to test performance of the proposed model.
International Journal of Logistics Systems and Management, 2018
In this paper, we propose a methodology to optimally configure a supply chain when considering a new product design. The supply chain configuration is conducted during the product design phase. In fact, several product design alternatives are possible and the aim is to select the best product design optimising the supply chain and satisfying market place as well. In this design problem, specificities of the new product architecture and logistical constraints of supply chain partners are considered at the same time. This product-supply chain design process simultaneity is modelled using an UML sequence diagram. Supply chain design is achieved by levels corresponding to the product's bill of material. A mathematical model is proposed for optimising costs for each level. Genetic algorithms are used to solve the complexity of the model. Since parameters values of genetic algorithms have a significant impact on their efficiency, we have proposed to combine Taguchi experimental design and genetic algorithm to determine the optimal combination of parameters that optimises the objective function. This method can effectively reduce time spent on parameter design using genetic algorithm and increase also its efficiency. The accuracy of the proposed GA-Taguchi method is validated using CPLEX software to evaluate its performance.