Mixed integer linear programming models for Flow Shop Scheduling with a demand plan of job types

This is a post-peer-review, pre-copyedit version of an article published in Central european journal of operations research. The final authenticated version is available online at: http://www.doi.org/10.1007/s10100-018-0553-8This paper presents two mixed integer linear programming (MILP) models that extend two basic Flow Shop Scheduling problems: Fm/prmu/Cmax and Fm/block/Cmax. This extension incorporates the concept of an overall demand plan for types of jobs or products. After using an example to illustrate the new problems under study, we evaluated the new models and analyzed their behaviors when applied to instances found in the literature and industrial instances of a case study from Nissan’s plant in Barcelona. CPLEX solver was used as a solution tool and obtained acceptable results, allowing us to conclude that MILP can be used as a method for solving Flow Shop Scheduling problems with an overall demand plan.Peer ReviewedPostprint (published version

Exact and heuristic procedures for the Heijunka-flow shop scheduling problem with minimum makespan and job replicas

In this paper, a new problem of job sequences in a workshop is presented, taking into account non-unit demands for the jobs and whose objective is to minimize the total completion time for all the jobs (Cmax) satisfying a set of restrictions imposed on the problem to preserve the production mix. Two procedures are proposed to solve the new problem: Mixed Integer Linear Programming and a Metaheuristic based on Multistart and Local Search. The two proposed procedures are tested using instance set Nissan-9Eng.I, in both cases giving rise to highly satisfactory performance both in quality of solutions obtained and in the CPU times required. Through a case study of the Nissan engine manufacturing plant in Barcelona, our economic-productive analysis reveals that it is possible to save an average of € 1162.83 per day, manufacturing 270 engines, when we transform the current assembly line into a Heijunka-Flow Shop.Peer ReviewedPostprint (published version

Bounded dynamic programming approach to minimize makespan in the blocking flowshop problem with sequence dependent setup times

This paper aims at presenting an algorithm for solving the blocking flow shop problem with sequence dependent setup times (BFSP-SDST) with minimization of the makespan. In order to do so, we propose an adapted Bounded Dynamic Programming (BDP-SN) algorithm as solution method, since the problem itself does not present a significant number of sources in the state-of-art references and also because Dynamic Programming and its variants have been resurfacing in the flowshop literature. Therefore, we apply the modified method to two sets of problems and compare the results computationally and statistically for instances with a MILP and a B&B method for at most 20 jobs and 20 machines. The results show that BDP-SN is promising and outperforms both MILP and B&B within the established time limit. In addition, some suggestions are made in order to improve the method and employ it in parallel research regarding other branches of machine scheduling