Chair: Yuvraj Gajpal, Asper School of Business, University of Manitoba, Canada
Optimization of production scheduling in the mould making industry
Bárbara Esperança Virgílio (email@example.com), Marta Castilho Gomes (firstname.lastname@example.org), Ana Barbosa-Póvoa (email@example.com)
This paper presents OPTMESC, an integer linear programming model developed for production scheduling in the mould industry, which is based on discrete, make-to-order job shop production. The model was implemented in GAMS modelling system and solved with commercial software for real data from a mould making firm. Application is illustrated with a case study of a production plan involving parts from various moulds. The good computation times needed to solve the model to optimality make this study a promising first step towards development of a decision support system for production scheduling in the mould industry.
Keywords: Scheduling, job shop, integer linear programming
A hybrid evolutionary algorithm to solve a hierarchical production/distribution problem
Herminia I. Calvete (firstname.lastname@example.org), Carmen Gale (email@example.com), Jose A. Iranzo (firstname.lastname@example.org)
This research proposes a bilevel optimization problem to model the design of a distribution network that allows us to take into account how decisions made at the distribution stage of the supply chain can affect and be affected by decisions made at the manufacturing stage. The resulting model is a bilevel mixed integer optimization problem. In order to solve the optimization model, a metaheuristic approach based on evolutionary algorithms is developed. The algorithm combines the use of an evolutionary algorithm to control the supply of depots with optimization techniques to determine the delivery from depots to customers and the supply from manufacturing plants to depots. A computational experiment is carried out to assess the efficiency and robustness of the algorithm.
Keywords: Bilevel optimization, Evolutionary algorithm, Supply chain
Pseudo polynomial time algorithm for two agents scheduling problem with weighted completion time and makespan objectives
Yuvraj Gajpal (email@example.com), Shesh Narayan Sahu (firstname.lastname@example.org)
This paper considers a single machine scheduling problem, where two agents compete for the use of a single processing resource. Each of the agents need to process a set of jobs with the common resource to optimize their own objective function which depends on the completion time of its own jobs. The goal is to minimize the total weighted completion time of first agent subject to an upper bound on the makespan of the second agent. The problem is binary NP-hard. We propose a pseudo polynomial time algorithm to solve the problem. Numerical experiment is performed and the execution time is compared with the existing branch and bound method.
Keywords: scheduling, competing agents, polynomial time algorithm