P
Prakash L. Abad
Researcher at McMaster University
Publications - 43
Citations - 2552
Prakash L. Abad is an academic researcher from McMaster University. The author has contributed to research in topics: Reseller & Vehicle routing problem. The author has an hindex of 22, co-authored 42 publications receiving 2460 citations. Previous affiliations of Prakash L. Abad include College of Business Administration & University of Cincinnati.
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Optimal pricing and lot-sizing under conditions of perishability and partial backordering
TL;DR: In this article, a generalized model of dynamic pricing and lot-sizing by a reseller who sells a perishable good is formulated, where when it is economic to backlog demand, the reseller can plan for periods of shortage during which demand can be partially backordered.
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A joint approach for setting unit price and the length of the credit period for a seller when end demand is price sensitive
Prakash L. Abad,Chandra K. Jaggi +1 more
TL;DR: In this article, the authors consider the seller-buyer channel in which the end demand is price sensitive and the seller may offer trade credit to the buyer, and provide procedures for determining the seller's and the buyer's policies under non-cooperative as well as cooperative relationships.
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Optimal price and order size for a reseller under partial backordering
TL;DR: The pricing and/or lot sizing problem faced by a reseller is modeled assuming a general deterioration rate and a general demand function and the model allows for backlogging of demand.
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An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup
Yuvraj Gajpal,Prakash L. Abad +1 more
TL;DR: The proposed ACS algorithm uses a construction rule as well as two multi-route local search schemes to solve the vehicle routing problem with simultaneous delivery and pickup (VRPSDP) which is a combinatorial optimization problem.
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Optimal pricing and lot-sizing under conditions of perishability, finite production and partial backordering and lost sale
TL;DR: This paper uses a new approach to model backlogging of demand for perishable products, where customers are viewed to be impatient and the analysis presented for a perishable product is extended to the case in which the product is non-perishable.