Goda Ramkumar

The on-demand meal delivery business is getting very competitive and customer-centric day-to-day. This paper presents an optimization model for delivering orders with priority. The proposed model minimizes the Order to Delivery (O2D) time to provide a better Customer Experience (CX). A simulation model is developed to implement the priority delivery model along with standard delivery orders. The priority delivery model is simulated with actual food order data and performed a sensitivity… Show more

The on-demand meal delivery business is getting very competitive and customer-centric day-to-day. This paper presents an optimization model for delivering orders with priority. The proposed model minimizes the Order to Delivery (O2D) time to provide a better Customer Experience (CX). A simulation model is developed to implement the priority delivery model along with standard delivery orders. The priority delivery model is simulated with actual food order data and performed a sensitivity analysis to derive a few key managerial insights. The simulation result showed that the standard delivery orders’ CX and overall Cost Per Delivery (CPD) get impacted by an increase in the percentage of priority orders. Show less

The E-grocery delivery business is experiencing unprecedented growth owing to the current COVID pandemic situation. The trend is expected to remain the same, even after the situation is normal. The success of E-grocery depends on the cost-effectiveness and timely delivery of orders. This paper proposed a two-stage optimization framework for the scheduled E-grocery delivery-cost minimization. In the first stage, Last-Mile (LM) delivery optimization is modelled as a Pickup and Delivery Problem… Show more

The E-grocery delivery business is experiencing unprecedented growth owing to the current COVID pandemic situation. The trend is expected to remain the same, even after the situation is normal. The success of E-grocery depends on the cost-effectiveness and timely delivery of orders. This paper proposed a two-stage optimization framework for the scheduled E-grocery delivery-cost minimization. In the first stage, Last-Mile (LM) delivery optimization is modelled as a Pickup and Delivery Problem with Time Windows (PDPTW). This PDPTW problem is solved using a two-phase method comprising a construction heuristic (savings method) and a meta-heuristic (guided local search). The first stage returns a set of routes that optimizes the LM. The second stage solves the First-Mile delivery optimization problem using a multi-objective assignment model for assigning nearby Delivery Executives (DE) to the first stage's routes. Various practical business constraints, like DE bag volume, maximum weight, etc., are also considered. Sensitivity analyses are performed on the model parameters and found bag volume as a critical parameter for minimizing the cost. Two policies viz. overlapping slot (delivery slot are overlapping) and non-overlapping slot are compared. The overlapping slot is found to provide a relatively lower cost. This model is implemented in two Indian cities, exhibiting promising results (efficient delivery, cost-saving, giving another business case to invest in instant delivery). Show less

We consider the problem of product bundling (seats and ancillaries) in the context of offering the right products to airline customers at the right price and in the right manner, so as to best satisfy customer needs and maximize airline revenue. This problem falls on the cusp of airline revenue management (apropos controlling price and availability) and retail e-commerce (apropos bundle design and shopping session management); therefore, we synthesize ideas from both domains to devise a… Show more

We consider the problem of product bundling (seats and ancillaries) in the context of offering the right products to airline customers at the right price and in the right manner, so as to best satisfy customer needs and maximize airline revenue. This problem falls on the cusp of airline revenue management (apropos controlling price and availability) and retail e-commerce (apropos bundle design and shopping session management); therefore, we synthesize ideas from both domains to devise a solution framework. Our proposed solution is designed in a modular manner, so as to allow incremental and independent improvements to product design, pricing, and shopping session management. In this paper, we specifically focus on methodologies for offer construction: creating product bundles and estimating willingness to pay. We demonstrate the utility of these methodologies through illustrative results on real and simulated datasets. Show less

“O&D RM provides incremental revenue benefits compared to Leg RM” – the statement has been proven through many simulation studies and many airlines have implemented and reported the benefits from O&D RM. The key value driver of this benefit is the network optimization model that uses O&D forecasts and market representative fares to do effective trade-offs. There are a multitude of factors that are at play in ensuring the proposed benefits from O&D RM are materialized. Some of the key challenges… Show more

“O&D RM provides incremental revenue benefits compared to Leg RM” – the statement has been proven through many simulation studies and many airlines have implemented and reported the benefits from O&D RM. The key value driver of this benefit is the network optimization model that uses O&D forecasts and market representative fares to do effective trade-offs. There are a multitude of factors that are at play in ensuring the proposed benefits from O&D RM are materialized. Some of the key challenges that airlines face today are the complexity of forecast management, maintaining accurate fares for optimization, and using advanced availability processors to achieve this goal. The other major challenge is the big organizational change from Leg mode to O&D mode among the managers and RM analysts. Additionally, distribution aspects such as seamless availability, married segments, and journey controls also play an important role in effectively reaping the benefits of O&D RM. In this study, we leverage APOS (Airline Planning and Operations Simulator) of Sabre and analyze how each of these factors impacts the O&D RM value across different load factors and flow traffic levels Show less

Airline partnerships have become one of the major trends in the recent years with the primary motivation of increasing revenues and decreasing costs for alliance partners. A major advantage comes through increase in the number of destinations served by an airline at little incremental costs. The total benefit of partnership can be achieved when partners in an alliance operate and take decisions as a single virtual entity. Various systems of the partner airlines need to interface and exchange… Show more

Airline partnerships have become one of the major trends in the recent years with the primary motivation of increasing revenues and decreasing costs for alliance partners. A major advantage comes through increase in the number of destinations served by an airline at little incremental costs. The total benefit of partnership can be achieved when partners in an alliance operate and take decisions as a single virtual entity. Various systems of the partner airlines need to interface and exchange information to achieve the benefit in a decentralized world. This paper provides a path to maturity in collaboration between partners from current state to joint revenue management leveraging simulation studies run on real data from two airline partners. The results from simulation studies quantify the revenue impact of incremental steps in maturity of collaboration along stages of information exchange, true origin and destination demand forecasting and revenue sharing agreements Show less

While today’s revenue management systems are increasingly sophisticated, there is no one-size-fits-all solution. An airline must regularly re-evaluate its business model against the many options available and invest time, effort and money to move from one mode of revenue management to the other. Each airline has its own specific business model and network structure, so estimating ‘return on investment’ from changes in revenue management methods based on academic literature or case studies from… Show more

While today’s revenue management systems are increasingly sophisticated, there is no one-size-fits-all solution. An airline must regularly re-evaluate its business model against the many options available and invest time, effort and money to move from one mode of revenue management to the other. Each airline has its own specific business model and network structure, so estimating ‘return on investment’ from changes in revenue management methods based on academic literature or case studies from other airlines may not be fully applicable. This article describes how the authors successfully employed simulation analysis tools to estimate the impacts of various revenue management methods when applied to an airline’s specific network and fare structure. For the six airlines considered in this study, the estimated revenue benefits of moving from leg-based to full-O&D controls ranged between 1 and 6 per cent improvement, and the simulation results helped us gain better insights into the factors affecting those benefits. Show less