K. Ganesh

A hybrid model for sourcing selection with order quantity allocation with multiple objectives under fuzzy environment

In the face of acute global competition, sourcing selection with order quantity allocation is rapidly growing as a vital issue to any organisation striving for success in business and sustainable competitive advantage. Sourcing selection is a complex multi criteria decision making problem and the complexity increases with the interdependence among the selection criteria. To model the uncertainties encountered in the integrated sourcing selection and order allocation methodology, fuzzy theory is adopted. A hybrid model with the integration of data envelopment analysis and genetic algorithm is proposed in this paper. The hybrid model is illustrated for a case study.

A model for selection of suppliers by comparison of two clustering algorithms

This paper deals with the study of consumer durables suppliers and retailers, and assessment of these suppliers with multiple products and multiple brands based on multiple criteria. The objective is to identify the set of suppliers for set of products. We develop two phase logical model. The first phase includes Fast-Slow-Non moving (FSN) and High-Medium-Low (HML). FSN and HML analysis were carried out to categorise the products. The second phase is the cluster analysis. We used two clustering methods, divisive and K-means clustering for comparison. Cluster analysis assists in selecting the final list of suppliers by parameterised clustering.

Development and assessment of modified VIKOR method for multi-criteria single sourcing in supply chain

The sourcing decision plays a major role in supply chain because raw materials/semi-finished goods cost constitute the key cost of final product. We develop a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, a compromise ranking model for evaluation and selection of sourcing partners to handle the conflicting and non-commensurable set of criteria and to identify the solution close to ideal. The modified VIKOR method is compared with two multi-criteria decision-making methods: technique for order preference by similarity to an ideal solution (TOPSIS) and elimination and choice translating reality (ELECTRE). All the three approaches were illustrated and compared for a computer retail supply chain case study. The better results of modified VIKOR are validated.

Multi-phase composite analytical model for integrated allocation-routing problem – application of blood bank logistics

The integrated problem of allocating and routing blood for a public and private health care system is addressed. We modelled the problem as multiple-vehicle, multi-depot, multi-criteria allocation-routing problem which is termed as integrated allocation-routing (IAR) problem. We propose a three-phase composite analytical model (CAM) to solve IAR problem for public sector blood banks and five-phase CAM for private sector blood banks. Models are developed based on the integration of analytic hierarchy process and mixed-integer linear programming model. Quality of both models is evaluated on randomly generated datasets and a real-life case study.

Heuristic approach for balanced allocation problem in logistics: a comparative study

The core issue of this paper is efficient balancing of allocation of customers among multiple distribution centres. Allocation involves clustering of customers in such a way that the associated resources in terms of cost and time are minimal. Ready solution to this problem could be through nondeterministic polynomial (NP)-hard type model. But NP-hard type model is inherently time consuming in arriving at an optimal solution. This paper compares the meta-heuristic genetic algorithm with an improvised heuristic scheme developed from the 2-opt heuristic model. Possible solutions for efficient clustering of customers are then proposed.

Logical approach for evaluation of supply chain alternatives

The supply chain of manufacturing industry has been under constant pressure to improve competitiveness, and supply chain network design is generally seen as one of the important means of resolution. The design or redesign of supply chain network entails taking decisions on a range of strategic issues, including the selection of suppliers, choosing the transportation link/node, location and selection of warehouses, etc. Total cost to serve is often used as the major factor in evaluation of supply chain network design, whereas enough attention in including the importance of customers for the evaluation of network remains challenging. The purpose of this study is to propose a logical approach by which the importance of customer weightage can be included in the evaluation of supply chain network design. The logical approach uses the Analytic Hierarchy Process (AHP) technique for evaluation. The logical approach is demonstrated with a numerical example.

REFING: heuristic to solve bi-objective resource allocation problem with bound and varying capacity

One of the important extensions of the classical multi-commodity network flow (MCNF) problem in bi-objective resource allocation problem with bound and varying capacity (BORAPBVC). We developed a recursive function inherent genetic algorithm (REFING) to solve MCNF problem and BORAPBVC. The objective of BORAPBVC problem is to find the optimal allocation with the consideration of two objectives and lower and upper bound as the service limit in the serving nodes with varying capacity. The REFING heuristic is tested for randomly generated datasets of BORAPBVC. When compared with the results of brute force method, REFING has performed better both in terms of solution quality and computational time.

Comparison of fuzzy C-mean clustering and 0-1 integer programming model for employee routing problem

In a real time life, vehicle routing problems (VRP) arises whenever a set of vehicles is available to serve a set of transportation requests. The work carried in this paper focuses on understanding the concept of VRP and applying the techniques to a real time problem, which relates to the picking up of employees of an organisation by a fleet of buses. The problem is modelled as a employee routing problem (ERP), i.e., each bus has a limited number of seats and the number of employees picked up by each bus should be less than or equal to the maximum capacity of the bus. The techniques used here are Fuzzy C-mean clustering and 0-1 integer programming model for obtaining the allocation of employees to each bus. The other techniques include nearest neighbourhood, which is used to obtain the initial route for the buses and 2-opt method, which is used to improve the travelling route by reducing the total cost and thus it helps in achieving the objective of ERP.

Bidding process and integrated fuzzy model for global sourcing based on customer preferences

Due to the increasing competition of globalisation and fast technological improvements, world markets demand companies to have quality and professional supply chain partners. This can only be achieved by employing potential bidding process for global sourcing. In this paper, we proposed a generic bidding process with respect to customer preferences for global sourcing. We develop an integrated fuzzy model leveraging fuzzy analytic hierarchy process and data envelopment analysis based on the model of Parthiban et al. (2008) for evaluation and selection of supply chain partner for global sourcing. The integrated fuzzy model is applied and illustrated for a real-life case study. A practical computer-based decision support system is developed for the model to help managers make better decisions under fuzzy circumstances.

MASS: an analytical model for assessment of supply chain entity

Supply chain decision makers frequently consider the use of quantitative models for decision support when they face supply chain network design related decisions. This paper presents a generic analytical model derived with the base of Brown and Gibson (1972) model that incorporates the effects of both objective and subjective factors for evaluation of supply chain entity. The model shaped in such a way that it could be used in either an educational setting or in industry for making supply chain network design decisions. From the teaching feature, faculty and students can look at a supply chain network and can understand the consequences of adjustments without having to experience it firsthand. Industry professionals can modify the model to make it more like their own supply chain network and also can understand the effects of varying the attributes. Analytical model is illustrated with a real life example case.