A new constructive heuristic for the Fm|block|¿T

This paper deals with the blocking flow shop problem and proposes new constructive procedure s for the total tardiness minimization of jobs. The heuristic has three - phases to build the sequence; the first phase selects the first job to be scheduled, the second phase ar ranges the remaining jobs and the third phase uses the insertion procedure of NEH to improve the sequence. T he proposed proce- dures evaluate the tardiness associated to the sequence obtained before and after the third phase in order to keep the best of both because , we have observed , that the insertion phase can worsen the result . The c omputational evaluation of these procedures against the benchmark constructive procedures from the literature re- veals their good performancePostprint (published version

A New Constructive Heuristic for the Fm|block|ST

This paper deals with the blocking flow shop problem and proposes new constructive procedures for the total tardiness minimization of jobs. The heuristic has three-phases to build the sequence; the first phase selects the first job to be scheduled, the second phase arranges the remaining jobs and the third phase uses the insertion procedure of NEH to improve the sequence. The proposed procedures evaluate the tardiness associated to the sequence obtained before and after the third phase in order to keep the best of both because the insertion phase can worsen the result. The computational evaluation of these procedures against the benchmark constructive procedures from the literature reveals their good performance.Postprint (published version

Flowshop scheduling problems with due date related objectives: A review of the literature

3rd International Conference on Industrial Engineering and Industrial Management XIII Congreso de Ingeniería de Organización Barcelona-Terrassa, September 2nd-4th 200

An effective hybrid ant lion algorithm to minimize mean tardiness on permutation flow shop scheduling problem

This article aimed to develop an improved Ant Lion algorithm. The objective function was to minimize the mean tardiness on the flow shop scheduling problem with a focus on the permutation flow shop problem (PFSP). The Hybrid Ant Lion Optimization Algorithm (HALO) with local strategy was proposed, and from the total search of the agent, the NEH-EDD algorithm was applied. Moreover, the diversity of the nominee schedule was improved through the use of swap mutation, flip, and slide to determine the best solution in each iteration. Finally, the HALO was compared with some algorithms, while some numerical experiments were used to show the performances of the proposed algorithms. It is important to note that comparative analysis has been previously conducted using the nine variations of the PFSSP problem, and the HALO obtained was compared to other algorithms based on numerical experiments

An efficient hybrid iterated local search algorithm for the total tardiness blocking flow shop problem

This paper deals with the blocking flow shop problem and proposes an Iterated Local Search (ILS) procedure combined with a variable neighbourhood search (VNS) for the total tardiness minimization. The proposed ILS makes use of a NEH-based procedure to generate the initial solution, uses a local search to intensify the exploration which combines the insertion and swap neighbourhood and uses a perturbation mechanism that applies, d times, three neighbourhood operators to the current solution to diversify the search. The computational evaluation has shown that the insertion neighbourhood is more effective than the swap one, but it also has shown that the combination of both is a good strategy to improve the obtained solutions. Finally, the comparison of the ILS with an Iterated greedy algorithm and with a greedy randomized adaptive search procedure has revealed its good performance.Preprin

Minimizing Total Tardiness in the m-Machine Flow-Shop Problem by Heuristic Algorithms

In this work the m-machine permutation flow-shop problem has been considered. The permutation flow-shop scheduling problem where a set of jobs have to be scheduled on a set of machines in the same order. We propose  heuristic algorithms for the flow-shop problem to minimizing the total tardiness. A new genetic and Tabu search algorithm which initialized by the solution of EDD, NEH and EN algorithm. Computational experiments are performed on benchmark instances and the results show the good performances of these methods. Finally, some future research directions are given

Trajectory Scheduling Methods for minimizing total tardiness in a flowshop

AbstractIn this paper, Trajectory Scheduling Methods (TSMs) are proposed for the permutation flowshop scheduling problem with total tardiness minimization criterion. TSMs belong to an iterative local search framework, in which local search is performed on an initial solution, a perturbation operator is deployed to improve diversification, and a restart point mechanism is used to select the new start point of another cycle. In terms of the insertion and swap neighborhood structures, six composite heuristics are introduced, which exploit the search space with a strong intensification effect. Based on purely insertion-based or swap-based perturbation structures, three compound perturbation structures are developed that construct a candidate restart point set rather than just a single restart point. The distance between the current best solution and each start point of the set is defined, according to which the diversification effect of TSMs can be boosted by choosing the most appropriate restart point for the next iteration. A total of 18 trajectory scheduling methods are constructed by different combinations of composite heuristics. Both the best and worst combinations are compared with three best existing sequential meta-heuristics for the considered problem on 540 benchmark instances. Experimental results show that the proposed heuristics significantly outperform the three best existing algorithms within the same computation time

Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times

In this paper, we consider a flowshop scheduling problem with sequence-dependent setup times and a bicriteria objective to minimize the work-in-process inventory for the producer and to maximize the customers' service level. The use of a bicriteria objective is motivated by the fact that successful companies in today's environment not only try to minimize their own cost but also try to fulfill their customers' need. Two main approaches, permutation and non-permutation schedules, are considered in finding the optimal schedule for a flowshop. In permutation schedules the sequence of jobs remains the same on all machines whereas in non-permutation schedule, jobs can have different sequence on different machines. A linear mathematical model for solving the non-permutation flowshop is developed to comply with all of the operational constraints commonly encountered in the industry, including dynamic machine availabilities, dynamic job releases, and the possibility of jobs skipping one or more machines, should their operational requirements deem that it was necessary. As the model is shown to be NP-hard, a metasearch heuristic, employing a newly developed concept known as the Tabu search with embedded progressive perturbation (TSEPP) is developed to solve, in particular, industry-size problems efficiently. The effectiveness and efficiency of the search algorithm are assessed by comparing the search algorithmic solutions with that of the optimal solutions obtained from CPLEX in solvable small problem instances.Keywords: Sequence-dependent setup time, Mixed-integer linear programming, Non-permutation scheduling, Flowshop, Tabu search with embedded progressive perturbations, Bicriteri

Tabu search for total tardiness minimization in flowshop scheduling problems

This work addresses the permutation flowshop scheduling problem with the objective of minimizing total tardiness. First, the behavior of solutions for small problems is analyzed for different due date scenarios. Then a tabu search-based heuristic is proposed as a method to explore the solution space. Diversification, intensification, and neighborhood restriction strategies are evaluated. Computational tests are presented and comparisons with the NEH algorithm and with a Branch-and-Bound algorithm are made. (C) 1998 Elsevier Science Ltd. All rights reserved.26321923