Subramanian Nachiappan

A genetic algorithm for optimal operating parameters of VMI system in a two-echelon supply chain

Abstract This paper deals with the operational issues of a two-echelon single vendor–multiple buyers supply chain (TSVMBSC) model under vendor managed inventory (VMI) mode of operation. The operational parameters to the above model are: sales quantity and sales price that determine the channel profit of the supply chain, and contract price between the vendor and the buyer, which depends upon the understanding between the partners on their revenue sharing. In order to find out the optimal sales quantity for each buyer in TSVMBSC problem, a mathematical model is formulated. Optimal sales price and acceptable contract price at different revenue share are subsequently derived with the optimal sales quantity. A genetic algorithm (GA) based heuristic is proposed to solve this TSVMBSC problem, which belongs to nonlinear integer programming problem (NIP). The proposed methodology is evaluated for its solution quality. Furthermore, the robustness of the model with its parameters, which fluctuate frequently and are sensitive to operational features, is analysed.

Examining the interrelationships between supply chain integration scope and supply chain management efforts

In this article, we study the concept of supply chain integration scope by comparing firms that involve immediate supply chain partners in their strategic efforts (narrow supply chain scope) versus firms that involve supply chain partners beyond the immediate level, for example second tier suppliers and end customers (broad supply chain scope). By relying on Coordination Theory and expanding upon Frohlich and Westbrooks (2001) ‘arcs of integration’ principle, we propose that supply chain integration scope and the type of supply chain management efforts deployed by firms are correlated. We use data from a large sample of US and European firms to explore the association between supply chain integration scope and supply chain management efforts. The results show that supply chain integration scope can be predicted by a firms supply chain management efforts. The implications of our results for practising managers are also offered. Our results suggest that supply chain managers should consider the practices identified in this study while deciding on the appropriate level of supply chain integration scope, i.e., which extended supply chain members to include in their strategic planning efforts.

Reverse Logistics network design: a review on strategic perspective

Reverse Logistics (RL) is the process of planning, implementing, and controlling the efficient, cost effective flow of obsolete materials referred to here as raw material, in-process inventory, finished goods and related information from the point of consumption to the point of origin for the purpose of recapturing value or proper disposal. The objective of this paper is to develop a framework to classify the various issues/parameters affecting strategic level decisions in RL and also to explore future research opportunities. The review serves as a guide to practitioners on the model and methodologies available to support better strategic level decisions in RL and reveals the potential scope of research for academics.

Key success factors and their performance implications in the Indian third-party logistics (3PL) industry

This paper uses the extant literature to identify the key success factors that are associated with performance in the Indian third-party logistics service providers (3PL) sector. We contribute to the sparse literature that has examined the relationship between key success factors and performance in the Indian 3PL context. This study offers new insights and isolates key success factors that vary in their impact on operations and financial performance measures. Specifically, we found that the key success factor of relationship with customers significantly influenced the operations measures of on-time delivery performance and customer satisfaction and the financial measure of profit growth. Similarly, the key success factor of skilled logistics professionals improved the operational measure of customer satisfaction and the financial measure of profit growth. The key success factor of breadth of service significantly affected the financial measure of revenue growth, but did not affect any operational measure. To further unravel the patterns of these results, a contingency analysis of these relationships according to firm size was also conducted. Relationship with 3PLs was significant irrespective of firm size. Our findings contribute to academic theory and managerial practice by offering context-specific suggestions on the usefulness of specific key success factors based on their potential influence on operational and financial performance in the Indian 3PL industry.

Knowledge management system for operating parameters in two-echelon VMI supply chains

This paper presents an information technology (IT)-driven normative model of vendor-managed inventory system in a two-echelon supply chain comprising of m vendors and n buyers, referred as Two-echelon Multiple Vendor Multiple Buyers Supply Chain (TMVMBSC). The operational parameters to the above model are: sales quantities and their corresponding sales price of the buyers and transaction quantities that determine channel profit of supply chain and their respective contract prices between vendors and buyers. In order to find out the optimal transaction quantities for each buyer in TMVMBSC problem, a mathematical model is formulated. Optimal sales price and acceptable contract price at different revenue share are subsequently derived with the optimal transaction quantity. A knowledge management system (KMS) using genetic algorithm is proposed to solve this TMVMBSC problem, which belongs to nonlinear integer programming problem (NIP). The proposed KMS is evaluated for its solution quality and computational time. Besides, the robustness of model with its parameters, which fluctuate frequently and are sensitive to operational features, is analysed.

Supplier assessment based on corporate social responsibility criteria in Indian automotive and textile industry sectors

Mandatory disclosure of corporate social responsibility (CSR) reporting forces supply chain members to consider CSR issues in developed countries. Researchers have viewed CSR content within different themes, such as human (social), ethical and environmental perspectives. So far, in India, very little research has been done to study the impact of human issues in employment (social), ethical issues in business operations and pollution (environmental) issues at both regional and specific sector level. This paper emphasises the perspective view of supplier selection, considering CSR issues as opposed to traditional methods using conventional selection criteria such as cost, quality, delivery and service. It employs six CSR criteria such as discrimination, abuse of human rights, child labour, long working hours, unfair competition and pollution to assess small- and medium-sized suppliers who produce and deliver products to the automotive and textile industry sectors. The results of this study indicate that to prevent discrimination against pay variation, minimise cases of abuse of human rights and incidence of child labour, suppliers must put in place proper policies and procedures regarding employment contract, identification and verification records. Furthermore, to reduce unfair competition, suppliers of both automotive and textile sectors may introduce processes for investigating reports of unethical conducts and take severe disciplinary action. The suppliers of both automotive and textile sectors believe that the competitive advantage can be achieved through environmental oriented business practices. However, they differ in their approaches in attaining this objective.

Efficient mechanism development for multirobot coordination

Mobile robots are indispensable in computer integrated manufacturing systems which involve flexible automation. Hence robot teams working together on tasks should be made to share the workload efficiently in a cost effective manner. The current scenario is handicapped as it considers only the distance between the robots and the targets, and not much importance is given to the utilisation of the robots. This drawback can be eliminated with the adoption of the proposed methodology. This work formulates a mathematical model and presents a novel approach for multirobot coordination using combinatorial auctions in order to maximise robot utilisation while minimising incurred costs. For coordination tasks robots are considered as bidders and targets are considered as the items to be bid. A simulator has also been created for the same using Visual Basic System. The proposed mechanism is illustrated with a suitable example and the robustness of the mechanism is validated.

Development of efficient combinatorial auction mechanism for airport slot allocation

The current allocation of slots in congested airports is fraught with deficiencies because of the liberalisation of air transportation undertaken all over the world. The existing grandfather rights rule is slowly being replaced with auctions. In the airport slot allocation problem, in order to effectively auction the slots, multiple-item auctions are employed. It is in this aspect that combinatorial auctions are employed, as they are the most efficacious in dealing with complimentarity. Since the existing mechanisms are more inclined towards maximising the auctioneers profit – with the monetary issue being the only concern – they lead to biased allocations. Therefore, this paper develops a model and proposes a mechanism that could overcome the shortcomings of the existing auctioning procedures by incorporating the concepts of welfare issues with due consideration given to the flight capacity to effectively allot the slots.

Balancing multi-robot prioritized task allocation: A simulation approach

Multi robot task allocation is a fundamental problem in robotics. Mostly multi robot task allocation (MRTA) problems concentrate on the minimization of the total distance travelled by the robots (Robot centered). Due attention is required for task centered allocation (task priority). A lot of real life application such as robotic search and rescue missions, environmental or hazardous clean-up missions emphasizes the priority of task allocation and balancing the utilization of robots. This paper develops a simulation model involving task priority and the utilization of robots and refers to it as a Balance multi-robot prioritized task allocation (BMRPTA) problem. The performance of the model is evaluated based on the minimum average waiting time and the completion time objective which ensures there would be a reasonable path balancing between the robots. Analysis has been carried out to study the effect of task priority on robot utilization.

A Heuristic for Heterogeneous Capacitated Pick-up and Delivery Logistics Problems with Time Windows in Agile Manufacturing and the Distribution Supply Chain

One type of decision of major importance that directly affects the performance of an agile manufacturing and distribution supply chain is the routing and scheduling of delivery trucks. Routing of vehicles leads to optimisation of logistics operations in enterprise networks. The present study addresses multiple-vehicle pick-up and delivery problems with time windows and heterogeneous capacitated vehicles (m-PDPTWH) for the application of blood bank logistics. The focus is to develop a heuristic to solve m-PDPTWH with the objective to maximise the number of requests assigned to vehicles routes and to minimise the total travel cost. Such a description scheme seems to be useful in the context of dynamic routing problems. The objective of this research is to provide a simple and fast meta-heuristic approach designed for the static case, before entrenching it in a dynamic context in future work. We choose simulated annealing (SA) as a search procedure to solve m-PDPTWH due to the reason that there is very limited literature on solving m-PDPTW using SA. Trials on a large number of test-problems have yielded encouraging results. The key contribution of the work is the development of a unified meta-heuristic to solve m-PDPTW and m-PDPTWH for large sized networks.