This research paper deals with the implementation of suitable meta-heuristic for the closed loop supply chain network design problem of a fashion product industry. First, the paper presents a comprehensive literature review on the applications of reverse and closed loop supply chain network design problems in Fashion Footwear Industry. The research work employs the case study approach to implement the model and algorithm. Closed loop supply chain network design problem of a Fashion Footwear Industry in South India is studied and considered for the purpose. Then it deals with the application of mathematical model and a suitable hybrid genetic algorithm (HGA) developed for the CLSC network design problem of the Industry this research. The MINLP model and suitable HGA developed are implemented in the industrial case as per the reverse supply chain process conditions and model adopted in the respective closed loop supply chain and the results are presented.
The fashion, leather and lifestyle products industries have been witnessing positive growth across all price points and product categories in India. The domestic companies manufacturing and marketing fashion and lifestyle products like footwear, hand bags, and other fashion life style accessories have registered a positive business growth in the recent past due to drastic increase in the consumption of these products among the domestic customers. This shift may be due to the modern fashion conscious consumers with variety seeking behaviours prefer to buy these products for different formal, casual and special occasions like good wedding celebrations, festival seasons, office usage, and for short and long domestic and international travels. The growth is remarkable in higher-end products, including fashionable footwear, trendy hand bags, and other fashion accessories. Across the channels, several new ranges were launched in all brands and price points, in both open and closed footwear categories with a special thrust on business collections, semi-formal footwear, and high fashion categories.
As the demand and consumption of the short lived footwear and leather accessories are in the upward trend, returns of these products from the customers for repairing or at the end of life is also increasing and becoming a difficult task for the industries to manage these returns. Due to the increase in the price and decrease in the supply of virgin raw materials and components, enforcement of eco-friendly regulations by the government, the companies are facing difficulties in manufacturing and marketing 100% fresh and virgin products at a very competitive and affordable price brackets to the consumers. The industries have started using the raw materials from alternate sources like recyclable materials, reusable components and re-furbish able or reconditioned products to manufacture and supply the products both for primary and secondary markets. Therefore, the integration of the both forward and reverse supply chain systems is gaining importance in the fashion product industries also and the companies are looking into developing an efficient supply chain models to implement the integrated supply chain concepts.
In this context, the closed loop supply chain model and hybrid genetic algorithm developed are very much in need for the present situations prevailing in the fashion product industries. The researcher approached a couple of industries who have shown interests to implement the CLSC network design model and Hybrid Genetic Algorithm developed for solving their supply chain network design problems. The industry shown interest has been considered for the purpose and thus, this paper deals with an industrial case study for the validation of the HGA developed to suit the real life situations. The Case Study discusses and presents the implementation of the CLSC model and hybrid genetic algorithm to solve the supply chain network design problem of a footwear industry which manufactures and supplies footwear made out of leather and non-leather materials to the domestic consumers in India. The company is located at Chennai in the state of Tamil Nadu, India.
The organization of this research paper is given as follows. The second section presents the literature review in the identified area. The third section formulates the objectives of the research work from the identified research gaps. Fourth section presents the appropriate methodology for implementing the research work. Fifth section describes the industry case, its problem statement, implementation of the model and hybrid genetic algorithm developed and discusses the end results by giving the optimum solution with illustrated shipment pattern for the identified problem of the footwear industry case. The final section concludes the research with a summary of findings.
The researchers surveyed the research works on the supply chain network design models and algorithms for the past 15 years and reviewed the literature on forward, reverse and closed loop supply chains. The literatures reviewed are dealt on the applications of models and algorithms in the fashion and footwear industry cases and presented in this section.
Fleischmann et al. [
Staikos and Rahimifard [
Crestanello and Tattara [
Ciarniene and Vienazindiene [
In this section, the literature review of the design of the closed loop supply chain system and reverse supply chain system in the Fashion Footwear Industry is presented. It is found that the researchers applied models, heuristics, genetic algorithms and hybrid GAs, and other heuristics to solve the supply chain network design problems. The outcome of the review shows that the meta-heuristics particularly the genetic algorithm and its hybrids are applied by the researchers to deal with the supply chain network design problems. The concepts of closed loop and reverse supply chains for the fashion products sectors like fashion footwear industry are in practice only in few developed countries, where the environmental legislations are very stringent. Very less research work has been done in these areas, which is evident from the case study literature reviewed. So, it is the need of the hour for the footwear industries to focus and implement these systems in order to sustain in the business with the growing problems of shortage of raw materials like leathers, soles, non-leather trims etc. to fulfill the domestic consumption and also to comply with the environmental regulations and legislations.
The statement of the research problem of the footwear industry case considered and the research objectives to be implemented for solving the CLSCND problem of the industry case are described in this section.
The closed loop supply chain network design model problem considered in this research is a multi-echelon and multi stage network design problem, which includes footwear manufacturers, footwear brand dealers, footwear brand retailers and first customers in the forward chain, and service/ repair centers, collector/dismantler/refurbisher (CDR), footwear remanufacturers, recyclers, disposal centers/land-fillers, footwear brand resellers and second customers in the reverse chain. The network deals with the two types of product returns, viz. product returns due to repair and product returns due to end-of-use or end-of-life in its reverse chain. The repair products are sent directly to the repair/service centre by the first customer for getting them repaired and the end-of-life (EOL) products are returned either directly or through the footwear brand retailer to the collector/dismantler/ re-furbisher by the first customer for re-processing. The returned products thus collected in the CDR locations are sorted and then the parts are dismantled and segregated into recoverable and non-recoverable or waste items. The recoverable items are again segregated into refurbishable, remanufacturable and recyclable items, and they are shipped to the respective facilities or locations for recovery process. The non-recoverable or the waste items are shipped to the disposal centers/land-fillers and disposed through land filling or incineration. The recovered products through the process of refurbishing and remanufacturing are shipped to the second customers via footwear brand resellers. The items recovered through recycling process are shipped to the raw material suppliers market by the recycler. In this context, the main aim of the CLSCND model considered in this research is to minimize the total cost of the integrated closed loop supply chain system which includes the costs of forward and reverse supply chains there by increasing the total profit of the closed loop network.
The research objectives of the closed loop supply chain network design problem identified for the footwear industry case considered in this research are furnished as follows.
1) To apply and compare the best GA based meta-heuristic with the mathematical model in terms of the total cost of the closed loop supply chain network to check its quality of solution with the optimal solution obtained by the mathematical model.
2) To propose and implement the application of the mathematical model at the first instance to obtain optimal solution in reasonable time for the closed loop network design problem of the Footwear Industry. If it is not possible to get the solution through the mathematical model for the case, then apply the best HGA to obtain very near optimal solution for the closed loop network design problem of the footwear industry case considered.
The methodology adopted for this research work is a combination of modeling, algorithmic and case study based research methods. The mathematical model and the meta-heuristic i.e. the hybrid genetic algorithm developed by Aravendan and Panneerselvam [
1) Modeling Research―Implementation of Mathematical Modeling:
The model developed for solving the closed loop supply chain network design problem by Aravendan and Panneerselvam [
2) Algorithmic Research―Implementation of Hybrid Genetic Algorithm
In the research works presented by Aravendan and Panneerselvam [
3) Case Study Research-Implementation of Fashion Footwear Industry Case
The industry case study presented in this research work is for the specific fashion product industry dealing with fashion footwear in South India. The model proposed has an objective to minimize the total cost of the integrated supply chain and also to reduce the wastage due to end of life goods returns from the customers. A descriptive and secondary research was applied to study and understand the company’s business profile and performance, its supply chain management strategies, frame work and implementation processes. The input data required for implementing the MINLP model and the best hybrid genetic algorithm (HGA4) proposed by Aravendan and Panneerselvam [
Due to the confidentiality agreement is being enforced between the company and researchers, the researchers have not disclosed the basic identities of the company and used a dummy company name for the industrial case study discussed in this section. All the data collected with respect to the company are used purely for academic and research purpose and not used for any commercial purpose.
India is ranked as the second largest footwear producer after China in the world with an annual production of 2200 million pairs. The country has a huge domestic retail market in which about 1950 million pairs are sold to fulfil the demands of the domestic consumers. The export of footwear is accounted for 45% share in India’s total leather and leather products export. The Footwear product mix consists of gents’ model for 55%, ladies model for 35% and children model for 10%.
The Footwear Industry is an ever growing and diversified manufacturing sector which applies a wide range of materials to make footwear ranging from different types and styles of footwear for all genders and age groups to more specialized footwear for special consumers like athletes, sports persons, kids, differently abled and old age people. Leather, Non-Leather materials like synthetic leathers, coated fabrics, rubber and textile materials are the basic materials most commonly used in footwear manufacture. These footwear materials are unique in their physical appearance, qualities, characteristics and performance, and require different treatments for using them to make virgin footwear for primary markets and reusable footwear secondary markets at the end of their life. The design, selection and application of footwear materials for the different types of footwear and the fabrication method significantly influence the life of the footwear and the scope for treating and managing the end of life product returns.
In the recent years, consumers demand a large variety of footwear for different occasions owing to their enhanced lifestyle and increased buying capacity. The market is very dynamic and the consumer preferences are very rapidly changing due to fashion awareness and trend adaptations among the consumers. Responsiveness to this consumer demands leads to the production of footwear with shorter product development cycle and shorter life cycle leading to a higher level of End-of-Life product returns and post-consumer waste. The amount of waste generated from the EOL product returns or the post-consumer footwear across the world is estimated to reach millions of tons per year, where a major share of it is disposed as wastes through incineration and land- fills. The footwear industry’s response to this increasing problem of EOL product returns and the post-consumer shoe wastes has been very poor or negligible which leads to major environmental pollution affecting the healthy and sustainable lifestyle of the society. It is the need of the hour for the footwear industries in India to rise to the situations and implement appropriate cost effective supply chain systems to tackle the growing environmental concerns by minimizing the wastage and total cost involved in the supply chain system. This could be achieved by managing the EOL product returns and post-consumer wastes efficiently through an integrated forward and reverse supply chains in a closed loop distribution network design in the footwear industry.
In this context, the researcher has approached a footwear industry in the state of Tamil Nadu, which has shown its concern over the problems due to post-consumer wastes and has shown interest to implement the closed loop supply chain network design model and suitable hybrid meta heuristic developed in this research work to manage the EOL product return issues in the Footwear Industry. Accordingly, the investigations and research works are carried out and the implementation process for the proposed footwear industry model is presented in the following sections.
The company, “XYZ Shoes Pvt. Ltd.” was established in late seventies in the state of Tamil Nadu and since then exporting formal, semi-formal and casual footwear to USA, UK and other European countries. The company’s product basket includes Ankle Boots, Formal Shoes based on Derby, Oxford, Monk and Brogue, Semi-Formal shoes based on Casual Slip-on and Moccasin styles. The company manufactures and exports mostly leather footwear with a combination of soling materials like Leather, Leather inserted PVCs, Poly-Urethane (PU), and Thermo Plastic Rubber (TPR), etc. The company markets footwear for both Gents and Ladies customers. As the domestic consumption of leather and non-leather footwear has been drastically increasing, the company has entered into the domestic market in the year 2010 by establishing a domestic brand in order to cater to the middle, upper middle and high class customers in India. The company has set up three manufacturing plants at the industrial estates in and around Chennai. The product basket for the domestic market includes formal, semi-formal and casual shoes and sandals made out of leather and combination materials. The company supplying variety of short lived fashion footwear in the semi-formal, casual and daily wear segments as these categories hold a major share of consumption by the domestic customers. The products are distributed to the end customers through the brand dealers, multi brand retailers and also through the company owned brand stores and franchisee stores.
The company has envisaged implementing an integrated closed loop supply chain system to minimize the total cost of the supply chain and to manage the growing end-of-life products due to the major consumption of short lived products. Therefore, the supply chain network model developed in this research work is customized and tailored to the requirement of the footwear industry considered in this case study. The illustration of the model as shown in
The proposed model is the formulation for the closed loop network design problem which integrates both forward and reverse logistics in the supply chain. The closed loop network presented in this research is a single product, single period (i.e. considered annually) and multi-echelon supply chain, which channelizes footwear manufacturers, footwear brand dealers, footwear brand retailers and first customers in the forward chain and channelizes repair/service centers, collectors/dismantlers/re-furbishers, remanufacturers, recyclers, land fillers, footwear brand resellers and second customers in the reverse chain. In the
The conditions and limitations of the proposed model are considered as follows.
1) The model is for a single product and single period network design.
2) The locations of the first customers and second customers are known and are with certain demands.
3) There is no shipment happening between the nodes in the same stage and the quantities of products returned are certain.
4) 50% the total quantity of footwear supplied are returned as EOL products and accounted for reverse process.
5) 30% of the total quantity of footwear supplied are returned as repair products by the customers and returned back to the customer after repairing for reuse.
6) 20% of the total quantity of the footwear supplied is not returned by the customers.
7) 40% of the EOL products are returned via footwear brand retailers and remaining 60% of the EOL products are returned directly, to the Collectors/Dismantlers/Re-furbishers (CDR).
8) Out of the total returned EOL products, 20% are re-furbishable items, 40% are re-manufacturable items, 25% are recyclable items and 15% are non-recoverable and disposed by land-fillers.
9) The quality of the remanufactured, refurbished and repaired products is different from that of the new products.
10) The locations of footwear manufacturers, footwear brand dealers, footwear brand retailers, collectors/dis- mantlers/re-furbishers, repair/service centers, recyclers, land fillers and footwear brand resellers and their capacities are known.
11) The costs parameters considered (viz., opening costs, operating costs, un-utilized capacity costs and transportation costs) are known for all the facilities and nodes.
12) The measure of quantity of products transported per trip is defined in the form of number of units per trip.
The closed loop supply chain model proposed for the footwear industry is a single period, single product and multi-echelon closed loop supply chain network design model. It has four echelons, viz. three manufacturers, three wholesalers, three retailers, six first customers in the forward chain and five echelons in the reverse chain, viz. two repair centres, two collectors/dismantlers/re-furbishers (hybrid), two recyclers, two land-fillers, three re- manufacturers (hybrid), two resellers and three second customers in the reverse chain as shown in
The distances between different pairs of facilities/nodes and that of between different pairs of facilities and customers (first customers, second customers) are given in Appendix 1.
First, the mathematical model presented by Aravendan and Panneerselvam [
Since, the mathematical model did not provide the optimum solution, next, the case study is solved using HGA4, which is presented by Aravendanand Panneerselvam [
Facilities/Nodes | No. | Facilities/Nodes | No. |
---|---|---|---|
Manufacturers/Remanufacturers (Hybrid centres) | 3 | Collectors/Dismantlers/Re-furbishers (Hybrid centres) | 2 |
Footwear Brand Dealers | 3 | Footwear Brand Resellers | 2 |
Footwear Brand Retailers | 3 | Recycler (3 PL) | 2 |
First customers | 6 | Land-filler (3 PL) | 2 |
Repair/Service centres (3 PL) | 2 | Second customers | 3 |
Parameters/Variables | Value | |
---|---|---|
Unit price of virgin/first products UP1, 100% | Rs.3000 | |
Unit price of second products UP2, 50% of UP1 | Rs.1500 | |
Total Demand of first customer D1, 100%, | 100,000 pairs | |
Total Demand of second customer D2, 30% of D1 | 30,000 pairs | |
Max return ratio of total EOL product returns to CDR FCDFEOLR, 50% of D1 | 50,000 pairs | |
Max return ratio of EOL returns to CDR via Retailer, 40% of EOLFRT | 20,000 pairs | |
Max return ratio of EOL returns directly to CDR 60% of EOLFCDR | 30,000 pairs | |
Max return ratio of repair products FCDFRR, 30% of D1 | 30,000 pairs | |
Land filling fraction CDRF1, 15% of EOLCDR | 7500 pairs | |
Recycling fraction CDRF2, 25% of EOLFCDR | 12,500 pairs | |
Re-Furbishing fraction (to Reseller) fraction CDRF3, 20% of EOLFCDR | 10,000 pairs | |
Remanufacturing fraction CDRF4, 40% of EOLFCDR | 20,000 pairs | |
Capacity of Manufacturer-1 | 35,000 pairs | |
Capacity of Manufacturer-2 | 35,000 pairs | |
Capacity of Manufacturer-3 | 40,000 pairs | |
Capacity of Footwear Brand Dealer-1 | 35,000 pairs | |
Capacity of Footwear Brand Dealer-2 | 33,000 pairs | |
Capacity of Footwear Brand Dealer-3 | 32,000 pairs | |
Capacity of Footwear Brand Retailer-1 | 35,000 pairs | |
Capacity of Footwear Brand Retailer-2 | 33,000 pairs | |
Capacity of Footwear Brand Retailer-3 | 32,000 pairs | |
Repair/Service Centre capacity | 30,000 pairs | |
Collector/Dismantler/Re-Furbisher capacity (CDR) | 50,000 pairs | |
Capacity of Re-Furbishers | 10,000 pairs | |
Capacity of Re-Manufacturer -1 | 6000 pairs | |
Capacity of Re-Manufacturer -2 | 7000 pairs | |
Capacity of Re-Manufacturer-3 | 7000 pairs | |
Capacity of Footwear Brand Reseller-1 | 15,000 pairs | |
Capacity of Footwear Brand Reseller-2 | 15,000 pairs | |
Capacity of Recycler-1 | 6250 pairs | |
Capacity of Recycler-2 | 6250 pairs | |
Capacity of Land-Filler-1 | 3750 pairs | |
Capacity of Land-Filler-2 | 3750 pairs | |
Opening costs/pair for Manufacturer 1 | Rs.1000 | |
Opening costs/pair for Manufacturer 2 | Rs.1200 | |
Opening costs/pair for Manufacturer 3 | Rs.1500 | |
Opening costs/pair for Footwear Brand Dealer 1 | Rs.500 | |
Opening costs/pair for Footwear Brand Dealer 2 | Rs.400 | |
Opening costs/pair for Footwear Brand Dealer3 | Rs.300 | |
Opening costs/pair for Footwear Brand Retailer 1 | Rs.200 | |
Opening costs/pair for Footwear Brand Retailer 2 | Rs.220 | |
Opening costs/pair for Footwear Brand Retailer 3 | Rs.200 | |
Opening costs/pair for Repair/Service Centre 1 | Rs.100 |
Opening costs/pair for Repair/Service Centre 2 | Rs.100 |
---|---|
Opening costs/pair for Collector/Dismantler/Re-furbisher 1 | Rs.200 |
Opening costs/pair for Collector/Dismantler/Re-furbisher 2 | Rs.180 |
Opening costs/pair for Remanufacturer 1 | Rs.400 |
Opening costs/pair for Remanufacturer 2 | Rs.450 |
Opening costs/pair for Remanufacturer 3 | Rs.500 |
Opening costs/pair for Recyclers | Rs.90 |
Opening costs/pair for Footwear Brand Resellers | Rs.100 |
Opening costs/pair for Land-Fillers | Rs.50 |
Operating costs/ pair for Manufacturer 1, | Rs.100 |
Operating costs/pair for Manufacturer 2 | Rs.130 |
Operating costs/pair for Manufacturer 3 | Rs.150 |
Operating costs/pair for Footwear Brand Dealer1 | Rs.120 |
Operating costs/pair for Footwear Brand Dealer2 | Rs.130 |
Operating costs/pair for Footwear Brand Dealer3 | Rs.120 |
Operating costs/pair for Footwear Brand Retailer 1 | Rs.50 |
Operating costs/pair for Footwear Brand Retailer 2 | Rs.50 |
Operating costs/pair for Footwear Brand Retailer 3 | Rs.50 |
Operating costs/pair for Repair/Service Centre 1 | Rs.50 |
Operating costs/pair for Repair/Service Centre 2 | Rs.50 |
Operating costs/pair for Collector/Dismantler/Re-Furbisher 1 | Rs.70 |
Operating costs/pair for Collector/Dismantler/Re-Furbisher 2 | Rs.80 |
Operating costs/pair for Remanufacturer 1 | Rs.80 |
Operating costs/pair for Remanufacturer 2 | Rs.90 |
Operating costs/pair for Remanufacturer 3 | Rs.100 |
Operating costs/pair for Recyclers | Rs.20 |
Operating costs/pair for Land fillers | Rs.10 |
Operating costs/pair for Footwear Brand Resellers | Rs.30 |
Transportation cost per kilometre/pair | Rs.1.00 |
un-utilized capacity costs for Manufacturer 1/ pair | Rs.220 |
un-utilized capacity costs for Manufacturer 2/ pair | Rs.230 |
un-utilized capacity costs for Manufacturer 3/ pair | Rs.250 |
un-utilized capacity costs for Re-Manufacturer 1/ pair | Rs.120 |
un-utilized capacity costs for Re-Manufacturer 2/ pair | Rs.130 |
un-utilized capacity costs for Re-Manufacturer 3/ pair | Rs.150 |
Steps of Hybrid Genetic Algorithms
The various steps implemented sequentially to develop the best hybrid genetic algorithm (HGA4) are furnished as follows.
Step 1: Input the following;
Number of stages = 11 (Footwear Manufacturers, Footwear Brand Dealers, Footwear Brand Retailers, First Customers, Repair Centers, Collector/Dismantler/Re-furbisher, Recycler, Land filler, Footwear Remanufacturers, Footwear Brand Resellers and Second Customers).
Maximum number of units/nodes in each stage from first to last stage (i.e. 3, 3, 3, 6, 2, 2, 2, 2, 3, 2 and 3, respectively) as genes of the chromosome.
Maximum number of successive populations to be generated (N) = 50.
Maximum number of Chromosomes in each population―population size (L) = 100.
The Generation Count, GC = 1.
Step 2: Apply the binary encoding method for the chromosomes to decide on the status (open or close) of the genes (units) in the Chromosomes.
Step 3: Generate a random initial population of L chromosomes (suitable solutions for the problem). Let it be a larger population, L = 100.
Step 4: Evaluate the Fitness function f(x) of each chromosome in the initial population L. The fitness function is as used in the mathematical model proposed in this research work, which is as given below.
Fitness Function Value (FFV) = OPC + OPRC + UCC + TC, where OPC = Opening Cost, OPRC = Operation Cost, UCC = Un-utilized Capacity Cost and TC = Transportation cost. (The Transshipment Algorithm, which is a combination of VAM method and U-V method, is incorporated to evaluate the transshipment cost of the fitness function).
Step 5: Sort the population L by the objective function (fitness function) value in the ascending order, because it is a minimization problem.
Step 6: Apply Elite Count (say top 2) and Rank selection. Select a given percentage (say 30%) from the top of the larger population L leaving the elite count, to form a sub-population S.
Step 7: Randomly pickup any two unselected parent chromosomes from the sub-population S. Let them be the parents x and y.
Step 8: Perform the crossover of the parents x and y to form their two new offspring x1 and y1 (Uniform crossover method is applied to form hybrid genetic algorithm, HGA4).
Step 9: Perform the mutation of each of the offspring x1 and y1 for a mutation probability Pm (say Pm = 0.06).
Step 10: Evaluate the fitness function value of each of the offspring x1 and y1. (The Transshipment Algorithm, which is a combination of VAM and U-V algorithms, is incorporated in the fitness function to evaluate the transshipment cost of the fitness function).
Step 11: Replace the parent chromosomes x and y along with their fitness function values in the larger population L with offspring x1 and y1 along with their fitness function values, respectively. (Here, weak parent replacement method is applied to form hybrid genetic algorithm, HGA4).
Step 12: Repeat Step 7 to Step 11 until all the chromosomes in the sub-population S are selected to create offspring.
Step 13: Increase the Generation Count (GC) by 1, i.e. GC = GC + 1.
Step 14: If GC ≤ N, then go to Step 5, else go to Step 15.
Step 15: Identify the chromosome in the larger population L, which has the best fitness function value and print the corresponding results.
Step 16: Stop.
On implementation, the best hybrid genetic algorithm(HGA4) is found to be very efficient in providing the solution in terms of processing time and it provided the optimized solution value of 0.6970369E+08 in just few seconds. The optimized flows of the solution thus obtained for the design of the closed loop supply chain network is illustrated in
In this section, the integrated foreword supply chain and reverse supply chains in the closed loop supply chain
network design of the Footwear Industry case is considered with the objective of minimizing the total costs of the entire supply chain distribution network. The MINLP model has been developed for the footwear industry case study and an attempt has been made to solve it using LINGO15 software. But it was observed that even after several hours of execution, this model did not give the final solution. Hence, the CLSC network design problem of footwear industry case was solved using HGA4 and the optimized solution with the corresponding optimized shipment pattern for the supply chain network design problem has been obtained and presented.
In this research work, the closed loop network design problem of fashion product industry case study i.e. case of a Footwear Industry is considered. In the implementation of the methods to solve the CLSC network design problem of the industry case study, first the mixed integer programming model has been applied to check whether the optimum solution could be obtained in reasonable time using LINGO 15. It was found that even after several hours of execution, the Lingo 15 software did not give the final solution for the closed loop supply chain network design problem. So, in the next stage, the case study problem has been solved using the best hybrid genetic algorithm (HGA4) developed for this purpose which provided the solution in just few seconds. The results obtained proved that, since the mathematical model could not provide the optimal solution in a reasonable period of time, the solution obtained by the implementation of the best hybrid genetic algorithm i.e. HGA4 has been assumed to be an optimal solution in terms of minimizing the total cost of the closed loop supply chain network problem of the fashion footwear industry.
The authors convey their heartfelt thanks and sincere gratitude to all the industry personnel for their excellent cooperation and support by providing the requisite data for conducting this research work. The authors also profusely thank the anonymous reviewers for their constructive and valuable feedback which are incorporated in this paper.
Muthusamy Aravendan,Ramasamy Panneerselvam, (2016) Application of Hybrid Genetic Algorithm for CLSC Network Design Problem in Fashion Footwear Industry—A Case Study Approach. Journal of Service Science and Management,09,195-210. doi: 10.4236/jssm.2016.93024
Footwear Brand Dealer J1 | Footwear Brand Dealer J2 | Footwear Brand Dealer J3 | |
---|---|---|---|
Manufacturer I1 | 7 | 16 | 25 |
Manufacturer I2 | 12 | 2 | 16 |
Manufacturer I3 | 37 | 29 | 13 |
Footwear Brand Retailer K1 | Footwear Brand Retailer K2 | Footwear Brand Retailer K3 | |
---|---|---|---|
Footwear Brand Dealer J1 | 9 | 15 | 21 |
Footwear Brand Dealer J2 | 4 | 7 | 13 |
Footwear Brand Dealer J3 | 21 | 22 | 6 |
FC L1 | FC L2 | FC L3 | FC L4 | FC L5 | FC L6 | |
---|---|---|---|---|---|---|
Footwear Brand Retailer K1 | 5 | 5 | 10 | 8 | 15 | 25 |
Footwear Brand Retailer K2 | 13 | 6 | 7 | 5 | 14 | 22 |
Footwear Brand Retailer K3 | 16 | 18 | 12 | 21 | 3 | 8 |
FC L1 | FC L2 | FC L3 | FC L4 | FC L5 | FC L6 | |
---|---|---|---|---|---|---|
Repair Center M1 | 5 | 4 | 13 | 6 | 17 | 27 |
Repair Center M2 | 6 | 7 | 8 | 10 | 10 | 20 |
FC L1 | FC L2 | FC L3 | FC L4 | FC L5 | FC L6 | |
---|---|---|---|---|---|---|
CDR N1 | 6 | 5 | 11 | 9 | 16 | 25 |
CDR N2 | 6 | 7 | 8 | 10 | 10 | 20 |
FC L1 | FC L2 | FC L3 | FC L4 | FC L5 | FC L6 | |
---|---|---|---|---|---|---|
Footwear Brand Retailer K1 | 5 | 5 | 10 | 8 | 15 | 25 |
Footwear Brand Retailer K2 | 13 | 6 | 7 | 5 | 14 | 22 |
Footwear Brand Retailer K3 | 16 | 18 | 12 | 21 | 3 | 8 |
Footwear Brand Retailer K1 | Footwear Brand Retailer K2 | Footwear Brand Retailer K3 | |
---|---|---|---|
CDR N1 | 2 | 9 | 17 |
CDR N2 | 7 | 6 | 12 |
Land Filler O1 | Land Filler O2 | |
---|---|---|
CDR N1 | 16 | 12 |
CDR N2 | 19 | 11 |
Recycler P1 | Recycler P2 | |
---|---|---|
CDR N1 | 13 | 12 |
CDR N2 | 18 | 11 |
Footwear Brand Reseller R1 | Footwear Brand Reseller R2 | |
---|---|---|
CDR N1 | 6 | 4 |
CDR N2 | 6 | 3 |
Remanufacturer I1 | Remanufacturer I2 | Remanufacturer I3 | |
---|---|---|---|
CDR N1 | 14 | 6 | 33 |
CDR N2 | 16 | 2 | 28 |
Footwear Brand Reseller R1 | Footwear Brand Reseller R2 | |
---|---|---|
Remanufacturer I1 | 11 | 16 |
Remanufacturer I2 | 7 | 3 |
Remanufacturer I3 | 37 | 29 |
SC S1 | SC S2 | SC S3 | |
---|---|---|---|
Footwear Brand Reseller R1 | 7 | 8 | 13 |
Footwear Brand Reseller R2 | 11 | 12 | 10 |