A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers

Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry

In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problem

A MATHEMATICAL MODEL FOR DELIVERY ZONE GROUPS BASED ON COURIER ASSIGNMENT OPTIMIZATION: A CASE STUDY IN A LOGISTICS SERVICE PROVIDER

Logistics service providers are the key stakeholder in Indonesian logistics activities that are growing significantly and face many challenges. In this research, a case study on a logistics service provider located in the city of Yogyakarta Indonesia is evaluated. The provider is currently experiencing rapid growth indicated by increasing delivery volume and scopes. However, optimal resource management has not been able to be adequately calculated, such as inefficient courier assignment and overloaded couriers' volume. Thus, this study aims to minimize total distances through optimal zone groups under several restrictions. An optimization approach is selected in this research by initially building a mathematical model using a standard form of linear programming. Then, the mathematical model is solved to generate minimum distances. The result indicated that the total minimum distances had been reached with considerable changes in delivery zone grouping, and the couriers' capacity was optimally utilized without overloaded capacity. These zone groups can be used as a reference for further research by taking into account some restrictions such as packages fluctuations as well as adding objective to minimize couriers' traveling time

Supplier selection in automobile industry: A mixed balanced scorecard–fuzzy AHP approach

AbstractThis study proposed an integrated Balanced Scorecard–Fuzzy Analytic Hierarchical Process (BSC–FAHP) model to select suppliers in the automotive industry. In spite of the vast amount of studies on supplier selection, the evaluation and selection of suppliers using the specific measures of the automotive industry are less investigated. In order to fill this gap, this research proposed a new BSC for supplier selection of automobile industry. Measures were gathered using a literature survey and accredited using Nominal Group Technique (NGT). Finally, a fuzzy AHP was used to select the best supplier