Ravi Ramya

Bio: Ravi Ramya is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Sizing & Crossover. The author has an hindex of 3, co-authored 7 publications receiving 21 citations.

Capacitated lot-sizing problem with production carry-over and set-up splitting: mathematical models

Abstract: This work proposes mathematical models (MMs) for the capacitated lot-sizing problem with production carry-over and set-up splitting, which can handle two scenarios, namely (1) situation/scenario where the set-up costs and holding costs are product dependent and time independent, and with no backorders or lost sales, and (2) situation where the set-up costs and holding costs are product dependent and time dependent, and with no backorders or lost sales. Previously, in an existing study the authors had developed a MM for the same problem and situation where the set-up costs and holding costs are product dependent and time independent, i.e. our Scenario 1. We compare our proposed models with the model in the existing study that appears to be incorrect.

Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods (CLSP:PCSC): Mathematical Model 1 (MM1) and a Heuristic for Process Industries

Abstract: The capacitated lot sizing problem (CLSP) is a lot sizing model in which the production of multiple products is allowed within a time period on a single machine, with a condition that the entire demand for a product within that period should be met from the production in that period and/or the inventory carried from the previous periods, without any backorders or lost sales. Finding a minimum cost production plan that satisfies all the demand requirements without exceeding the capacity limits of a period is the main objective of the CLSP.

Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods Assuming Sequence-Dependent Setup Times and Setup Costs (CLSP-SD-PCSC): Mathematical Models for Process Industries

Abstract: In Chaps. 3 and 4, mathematical models have been proposed for the capacitated lot sizing problem with production carryover and setup crossover across periods. Heuristics based on both the mathematical models have also been proposed. The models and heuristics address real-life situations in process industries such as production immediately after setup and uninterrupted production carryover across periods.

CLSP: Real Life Applications and Motivation to Study Lot Sizing Problems in Process Industries

Abstract: Generally, the CLSP addresses the production planning problem in discrete manufacturing industries and continuous manufacturing industries. A brief explanation about the production planning in discrete manufacturing industries and continuous manufacturing industries with relevant examples is presented in Sects. 2.1.1 and 2.1.2, respectively.

Capacitated lot-sizing with sequence dependent setup costs

Abstract: A new model is presented for capacitated lot-sizing with sequence dependent setup costs. The model is solved heuristically with a backward oriented method; the sequence and lot-size decisions are based on a priority rule which consists of a convex combination of setup and holding costs. A computational study is performed where the heuristic is compared with the Fleischmann approach for the discrete lot-sizing and scheduling problem with sequence dependent setup costs.

Parallel machine, capacitated lot-sizing and scheduling for the pipe-insulation industry

Abstract: We develop a solution procedure for a production problem that involves the optimal lot-sizing and scheduling of multiple products on parallel machines over a long planning horizon. The objective is...

Solving a Multi-Level Capacitated Lot Sizing Problem with Multi-Period Setup Carry-Over via a Fix-and-Optimize Heuristic

Abstract: This paper presents a new algorithm for the dynamic Multi-Level Capacitated Lot Sizing Problem with Setup Carry-Overs (MLCLSP-L). The MLCLSP-L is a big-bucket model that allows the production of any number of products within a period, but it incorporates partial sequencing of the production orders in the sense that the first and the last product produced in a period are determined by the model. We solve a model which is applicable to general bill-of-material structures and which includes minimum lead times of one period and multi-period setup carry-overs. Our algorithm solves a series of mixed-integer linear programs in an iterative so-called Fix-and-Optimize approach. In each instance of these mixed-integer linear programs a large number of binary setup variables is fixed whereas only a small subset of these variables is optimized, together with the complete set of the inventory and lot size variables. A numerical study shows that the algorithm provides high-quality results and that the computational effort is moderate.

Multi-level lot-sizing with setup times and multiple constrained resources: internally rolling schedules with lot-sizing windows

Abstract: In this paper a new time-oriented decomposition heuristic is proposed to solve the dynamic multi-item multilevel lot-sizing problem in general product structures with single and multiple constrained resources as well as setup times. While lot-sizing decisions are made sequentially within an internally rolling planning interval (or lot-sizing window), capacities are always considered over the entire planning horizon. For each submodel a model formulation based on the "Simple Plant Location" representation is developed. These mixed-integer linear submodels are solved by standard mathematical programming software even for relatively large test instances. Extensive computational tests show that the heuristic proposed provides a better solution quality than a well-known special purpose heuristic.