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Papers by Subodha Dharmapriya

Lecture notes in mechanical engineering, 2023

Zero hunger is one of the top three goals of Sustainable Development Goals which is achievable by... more Zero hunger is one of the top three goals of Sustainable Development Goals which is achievable by reducing the postharvest losses of the food supply chain and improving food security. In developing countries approximately 40% of fruit harvest goes to waste due to not having proper mechanisms, coordination and best practices and poor post-harvest management. A pilot study has found post-harvest losses of fresh fruits and vegetables occur in 2.29%, 1.57%, 6.22% and 7.89% at farmer, collection center, wholesaler and retailer respectively, emphasizing the need of a reconfiguration. Following good practices in handling, introducing suitable bulk packing methods, vehicle upgrades and development of different supply chain configurations are some approaches in mitigating postharvest losses. Therefore, it is timely to change the product flow of supply chain by reconfiguration. The existing configuration of fruit and vegetable supply chain is simulated as an agent based simulation model taking banana supply chain as a case study. Short supply chain branches were introduced as suggestions to avoid the congestion and banana getting exposed to mechanical damages. The reconfigured supply chain emitted 10% less GHG than the existing banana supply chain while achieving the efficiency in distribution flow.

International Journal of Industrial Engineering and Operations Management

PurposeThe purpose of this study is to develop a novel general mathematical model to find the opt... more PurposeThe purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.Design/methodology/approachThe network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.FindingsThe selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graph...

Journal of global operations and strategic sourcing, Mar 6, 2023

Sustainability

As the world is moving into a sustainable era, achieving zero hunger has become one of the top th... more As the world is moving into a sustainable era, achieving zero hunger has become one of the top three Sustainable Development Goals, applying a considerable amount of pressure on the agri-food systems to make decisions contemplating the sustainability dimensions. Accordingly, making effective supply chain decisions holistically while achieving sustainability goals has become a major challenge faced by the present agri-food systems. Thus, to address the challenge, a novel supply chain configuration addressing multiple supply chain decisions to reduce global warming potential (GWP) and post-harvest losses have been presented by taking the banana supply chain in Sri Lanka as a case study. In the proposed approach, farmers have been clustered based on their geo positions using K-Means clustering followed by route planning within clusters using a heuristics approach. Retailer points are catered by assigning to wholesalers optimally modeling as an assignment model and then route planning e...

Transportation, a vital logistics function, currently operating at a higher cost in industrial se... more Transportation, a vital logistics function, currently operating at a higher cost in industrial sector. Intelligent planning of transportation activities in distribution network with the assistance of Computational intelligence techniques is well understood a necessity. Here a Multi Depot Vehicle Routing Problem with Time Windows (MDVRPTW), which is NP-hard in nature, is considered. One of the meta-heuristics techniques: Simulated Annealing (SA) was tested with different modifications to derive at a high quality solution. Comparison has been carried out between adaptive and basic SA in order to show the importance of problem specific modifications of SA. Simulations were carried out on benchmark data and results revealed that improved SA out perform in the solution quality.

2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2016

Supply chain literature highlights the increasing importance of effective supply network configur... more Supply chain literature highlights the increasing importance of effective supply network configuration decisions that take in to account such realities as market turbulence and demand volatility, as well as ever expanding global production networks. Supply network configurations decisions that account for these contingencies are expected to meet the evolving needs of customers while delivering better outcomes for all parties involved. This paper presents the findings of a structured review of supply network configuration literature which is synthesized under the two categories, drivers of supply network configuration decisions and the key parameters considered in developing decision support tools. This review also included an evaluation of the tools used for supporting supply network configuration decisions. The paper identifies the areas for future research, as well as the decision support tools required for building supply network capacity to meet the challenges brought about by the changing business environment.

Co-ordination of warehouse operations efficiently is critical in the supply chain management of a... more Co-ordination of warehouse operations efficiently is critical in the supply chain management of all manufacturing industry. Lean tools and techniques are widely used in optimization problems where this study also the get the assistance of Lean techniques to optimize the warehouse operations. According to Lean thinking it can be decided that the efficiency of warehouse operations depends on the layout arrangement, material handling techniques and media of transportation. Therefore, this study attempts to optimize warehouse layout: by allocating an economical place to each type of item while minimizing the honeycombing. However, due to the computational complexity of finding an optimal allocation within reasonable time frame, this is mathematically termed as NP-hard type problems. It has been found in the literature that the heuristic approaches are highly attractive than the traditional approaches for this instances. The Simulated Annealing heuristic was used to determine the optimal...

IEEE Transactions on Engineering Management, 2019

This paper demonstrates the application of a novel multi-agent modelling approach to support supp... more This paper demonstrates the application of a novel multi-agent modelling approach to support supply network configuration (SNC) decisions towards addressing several challenges reported in the literature. These challenges include: enhancing supply network (SN)-level performance in alignment with the goals of individual SN entities; addressing the issue of limited information sharing between SN entities; and sustaining competitiveness of SNs in dynamic business environments. To this end, a multi-stage, multi-echelon SN consisting of geographically dispersed SN entities catering to distinct product-market profiles was modelled. In modelling the SNC decision problem, two types of agents, each having distinct attributes and functions, were used. The modelling approach incorporated a reverse-auctioning process to simulate the behaviour of SN entities with differing individual goals collectively contributing to enhance SN-level performance, by means of setting reserve values generated through the application of a genetic algorithm. A set of Pareto-optimal SNCs catering to distinct product-market profiles was generated using Non-dominated Sorting Genetic Algorithm II. Further evaluation of these SNCs against additional criteria, using a rule-based approach, allowed the selection of the most appropriate SNC to meet a broader set of conditions. The model was tested using a refrigerator SN case study drawn from the literature. The results reveal that a number of SNC decisions can be supported by the proposed model, in particular, identifying and evaluating robust SNs to suit varied product-market profiles, enhancing SC capabilities to withstand disruptions and developing contingencies to recover from disruptions. Keywords-supply network dynamics, supply chain design, supply network configuration Managerial relevance: Compared to the existing SNC decision support tools, the proposed modelling approach addresses three key challenges faced by decision makers. First, it ensures optimal SN-level performance when individual SN entities still aiming to satisfy their local goals such as organisation-specific competitive priorities. Second, it facilitates SNC decisionmaking leading to optimal SN-level performance with minimal information sharing among SN entities, which reflects the real-world situation of organisations' reluctance to disclose commercially sensitive information. Third, the model can be useful in facilitating SNC decisions to sustain competitiveness of SNs in a dynamic business environment, which is characterised by changing consumer requirements, disruptions and other forms of uncertainty. Overall, the proposed multi-agent optimisation model can be used to enhance SNC decisions by any SN entity, as well as other parties such as supply chain analysts or consultants.

2018 IEEE Technology and Engineering Management Conference (TEMSCON), 2018

2018 International Conference on Production and Operations Management Society (POMS), Dec 1, 2018

This paper proposes a multi-agent modelling approach that supports supply network configuration d... more This paper proposes a multi-agent modelling approach that supports supply network configuration decisions towards sustaining operations excellence in terms of economic, business continuity and environmental performance. Two types of agents are employed, namely, physical agents to represent supply entities and auxiliary agents to deal with supply network configuration decisions. While using the evolutionary algorithm, Non-dominated Sorting Genetic Algorithm-II to optimize both cost and lead time at the supply network level, agents are modelled with an architecture which consists of decision-making, learning and communication modules. The physical agents make decisions considering varying situations to suit specific product-market profiles thereby generating alternative supply network configurations. These supply network configurations are then evaluated against a set of performance metrics, including the energy consumption of the supply chain processes concerned and the transportation distances between supply entities. Simulation results generated through the application of this approach to a refrigerator production network show that the selected supply network configurations are capable of meeting intended sustainable goals while catering to the respective product-market profiles.

International Journal of Industrial and Systems Engineering, 2012

ABSTRACT Effective coordination of distribution operations of a manufacturing organisation is par... more ABSTRACT Effective coordination of distribution operations of a manufacturing organisation is paramount since it represents the major cost component of the logistic supply chain. To deal with high demand of orders with shorter lead time, distributed warehouse concept is introduced, and this is currently being practised. Furthermore, due to inherent deficiencies in vehicle routing problem (VRP), rules have been extended to accommodate large-scale orders by splitting the delivery. Time-constrained routing is relevant in an application where timely scheduled productions occur. Artificial intelligences based approaches are widely used in the literature to solve VRP problems with extensions. In this research, hybrid algorithm (SATS) is developed based on simulated annealing (SA) and Tabu search (TS) techniques to improve the solution quality of the complex multi-depot VRP with time windows and split delivery. The simulation results reveal that SATS outperforms in solution quality when it is compared with the result of Cordeau et al. (2001). Results reveal SATS gives best results for more than 50% instances.