A genetic algorithm for the mixed flow shop problem

In this thesis we present a new interesting version of the mixed flow shop se-quencing problem, which at the same time is a version of the classic flow shop,a very common topic on operations research.We propose a genetic algorithm to solve it that we will compare at the endwith a simple initial genetic-based algorithm previously design. For that wefirst focus on the crossover operator as we consider it the most challenging parton a sequencing problem. We study and compare 5 different crossover operatorsand we choose the one that performs better. Finally we calibrate the populationsize, the weight of mutation and crossover operators on the algorithm and alsothe mutations operator itself.The goal of the thesis is to better understand the specific mixed flow shopproblem version presented and design a genetic algorithm that clearly improvesthe performance of the initial algorith

Sequencing CONWIP flow-shops: Analysis and heuristics

In this paper, we address the backlog sequencing problem in a flow-shop controlled by a CON\VIP production control system with the objective to minimise the make span We characterise the problem and analyse its similarities and differences with the permutation flow-shop problem A comparison of same well-known flow-shop heuristics is carried out and a simple and fast dispatching rule is proposed. Regarding the more simple and faster heuristics, the proposed dispatching rule outperforms those commonly used for the permutation flow-shop problem. --Scheduling,Sequencing,Flow-Shop,Constant Work in Process (CONWIP),Heuristics,Dispatching Rules

Note on the blocking flow shop problem

We present some results attained with different algorithms for the Fm|block|Cmax problem using as experimental data the well-known Taillard instances

Approximation algorithms for the parallel flow shop problem

We consider the NP-hard problem of scheduling n jobs in m two-stage parallel flow shops so as to minimize the makespan. This problem decomposes into two subproblems: assigning the jobs to parallel flow shops; and scheduling the jobs assigned to the same flow shop by use of Johnson's rule. For m = 2, we present a 32-approximation algorithm, and for m = 3, we present a 127-approximation algorithm. Both these algorithms run in O(n log n) time. These are the first approximation algorithms with fixed worst-case performance guarantees for the parallel flow shop problem

New insights on the blocking flow shop problem

We present some results attained with different algorithms for the Fm|block|Cmax problem using as experimental data the well-known Taillard instances.Preprin