Archive ouverte UNIGE | last documents for author 'Simon Thevenin'https://archive-ouverte.unige.ch/Latest objects deposited in the Archive ouverte UNIGE for author 'Simon Thevenin'engReactive variable neighborhood searchhttps://archive-ouverte.unige.ch/unige:104849https://archive-ouverte.unige.ch/unige:104849Recent works have shown that the variable neighborhood search (VNS) algorithm can be improved by using a reactive component. A component is reactive if its behavior changes dynamically depending on the information obtained from the current run, or depending on the instance to solve. This paper gives a review of these recent works, and proposes a new scheme to select reactively the move used in the shaking step of VNS. This new mechanism is particularly relevant to solve problems involving various types of decisions. For instance, an application of the resulting Reactive-VNS to a short-term production-planning problem is given. Experimental results show that Reactive-VNS outperforms the classical VNS approach on the latter problem.Fri, 01 Jun 2018 13:30:36 +0200Learning variable neighborhood search for a scheduling problem with time windows and rejectionshttps://archive-ouverte.unige.ch/unige:104846https://archive-ouverte.unige.ch/unige:104846Variable neighborhood search is a local search metaheuristic that uses sequentially different neighborhood structures. This method has been successfully applied to various types of problems. In this work, variable neighborhood search is enhanced with a learning mechanism which helps to drive the search toward promising areas of the search space. The resulting method is applied to a single-machine scheduling problem with rejections, setups, and earliness and tardiness penalties. Experiments are conducted for instances from the literature. They show on the one hand the benefit of the learning mechanism (in terms of solution quality and robustness). On the other hand, the proposed method significantly outperforms state-of-the-art algorithms for the considered problem. Moreover, its flexibility allows its straightforward adaptation to other combinatorial optimization problems.Fri, 01 Jun 2018 13:15:14 +0200All-terrain tabu search approaches for production management problemshttps://archive-ouverte.unige.ch/unige:100778https://archive-ouverte.unige.ch/unige:100778A metaheuristic is a refined solution method able to find a satisfying solution to a difficult problem in a reasonable amount of time. A local search metaheuristic works on a single solution and tries to improve it iteratively. Tabu search is one of the most famous local search, where at each iteration, a neighbor solution is generated from the current solution by performing a specific modification (called a move) on the latter. The goal of this chapter is to present tabu search approaches with enhanced exploration and exploitationmechanisms. For this purpose, the following ingredients are discussed: different neighborhood structures (i.e., different types of moves), guided restarts based on a distance function, and deconstruction/reconstruction techniques. The resulting all-terrain tabu search approaches are illustrated for various production problems: car sequencing, job scheduling, resource allocation, and inventory management.Thu, 21 Dec 2017 16:18:22 +0100Model and metaheuristics for a scheduling problem integrating procurement, sale and distribution decisionshttps://archive-ouverte.unige.ch/unige:99560https://archive-ouverte.unige.ch/unige:99560This paper presents an integrated approach for short-term supply chain management (SCM) at a fast moving consumer goods production plant. The problem is to determine the production quantities, to provide a detailed production schedule, to trigger the relevant express deliveries of raw material, and to manage the distribution. We propose a linear integer model, which integrates all of these decisions within scheduling. To find high quality solutions in a reasonable amount of time, various solution methods are proposed, such as a greedy constructive heuristic, two tabu search metaheuristics, a basic variable neighborhood search and an enhanced one, which uses a variable shaking operator. Experiments on realistic instances show that the latter method is efficient and robust. This paper is a contribution to the SCM literature (indeed, only few references address the integration of short term decisions and to the general metaheuristics field (as the variable neighborhood search paradigm is extended).Thu, 23 Nov 2017 15:41:35 +0100Graph multi-coloring for a job scheduling applicationhttps://archive-ouverte.unige.ch/unige:92813https://archive-ouverte.unige.ch/unige:92813In this paper, we introduce a graph multi-coloring problem where each vertex must be assigned a given number of different colors, represented as integers, and no two adjacent vertices can share a common color. In the variant considered, the number of available colors is such that not all vertices can be colored. Furthermore, there is a bound on the number of vertices which can be assigned the same color. A gain is associated with each vertex and the first objective is to maximize the total gain over all colored vertices. Secondary objectives consider the sequence of colors assigned to each vertex. More precisely, the range and the number of interruptions must be minimized, where the range corresponds to the difference between the largest and smallest colors assigned to a vertex. This variant of the graph multi-coloring problem is of interest because it can model practical job scheduling applications. An integer linear programming formulation is first proposed to address small-size instances. A construction heuristic, as well as local search methods, are then reported to tackle larger instances. The local search methods are based on several neighborhood structures, each one focusing on a specific property of the problem. Different ways to combine these neighborhood structures are also investigated.Fri, 24 Mar 2017 15:40:50 +0100Makespan minimisation for a parallel machine scheduling problem with preemption and job incompatibilityhttps://archive-ouverte.unige.ch/unige:92812https://archive-ouverte.unige.ch/unige:92812In this paper, an extension of the graph coloring problem is introduced to model a parallel machine scheduling problem with job incompatibility. To get closer to real-world applications, where the number of machines is limited and jobs have different processing times, each vertex of the graph requires multiple colors and the number of vertices with the same color is bounded. In addition, several objectives related to scheduling are considered: makespan, number of preemptions, and summation over the jobs' throughput times. Different solution methods are proposed, namely, two greedy heuristics, two tabu search methods and an adaptive memory algorithm. The latter uses multiple recombination operators, each one being designed for optimizing a subset of objectives. The most appropriate operator is selected dynamically at each iteration, depending on its past performance. Experiments show that the proposed algorithm is effective and robust, while providing high quality solutions on benchmark instances for the graph multi-coloring problem, a simplification of the considered problem.Fri, 24 Mar 2017 15:38:15 +0100Order acceptance and scheduling with earliness and tardiness penaltieshttps://archive-ouverte.unige.ch/unige:91048https://archive-ouverte.unige.ch/unige:91048This paper addresses a production scheduling problem in a single-machine environment, where a job can be either early, on time, late, or rejected. In order acceptance and scheduling (OAS) contexts, it is assumed that the production capacity of a company is overloaded. The problem is therefore to decide which orders to accept and how to sequence their production. In contrast with the existing literature, the considered problem jointly takes into account the following features: earliness and tardiness penalties(which can be linear or quadratic), sequence-dependent setup times and costs, rejection penalties, and the possibility of having idle times. The practical relevance of this new NP-hard problem is discussed and various solution methods are proposed, ranging from a basic greedy algorithm to refined metaheuristics (e.g., tabu search, the adaptive memory algorithm, population-based approaches loosely inspired on ant algorithms). The methods are compared for instances with various structures containing up to 200 jobs. For small linear instances, the metaheuristics are favorably compared with an exact formulation using CPLEX 12.2. Managerial insights and recommendations are finally given.Fri, 13 Jan 2017 15:09:48 +0100Metaheuristics for constrained production scheduling problemshttps://archive-ouverte.unige.ch/unige:73544https://archive-ouverte.unige.ch/unige:73544In this thesis, high level metaheuristics are proposed to solve production scheduling problems. Production scheduling is a crucial function for companies, which helps to manage the operations at the production shop level. It aims to reduce the costs, to increase the service level to customers, and to achieve better production efficiency. The design of powerful optimization methods for such problems is then decisive for the competitiveness of the companies. This thesis is divided into five chapters which focus on different production scheduling problems. For each problem, an integer linear programming formulation is given, and various heuristics and metaheuristics are proposed and compared. The first two chapters concern an extension of the graph coloring problem, which is extended to correspond to realistic job scheduling problems. Chapters three and four are related to a single machine scheduling problem. The last chapter studies the integration of short term supply chain management decisions.Wed, 24 Jun 2015 12:04:01 +0200Tabu search for a single machine scheduling problem with rejected jobs, setups and deadlineshttps://archive-ouverte.unige.ch/unige:73316https://archive-ouverte.unige.ch/unige:73316This paper addresses a single machine scheduling problem with release dates, deadlines, setup costs and times, and the possibility to reject some jobs while encountering an abandon cost. The objective function to minimize is a sum of regular functions depending on the completion time of the jobs. The problem is inspired by a manufacturing scheduling problem. We design a greedy algorithm and a tabu search approach for the problem. We studied several restriction procedures. Realistic instances with up to 500 jobs are tackled.Tue, 23 Jun 2015 08:48:00 +0200Metaheuristics for a scheduling problem with rejection and tardiness penaltieshttps://archive-ouverte.unige.ch/unige:73267https://archive-ouverte.unige.ch/unige:73267In this paper, we consider a single-machine scheduling problem (P) inspired from manufacturing instances. A release date, a deadline, and a regular (i.e., non-decreasing) cost function are associated with each job. The problem takes into account sequence-dependent setup times and setup costs between jobs of different families. Moreover, the company has the possibility to reject some jobs/orders, in which case a penalty (abandon cost) is incurred. Therefore, the problem at hand can be viewed as an order acceptance and scheduling problem. Order acceptance problems have gained interest among the research community over the last decades, particularly in a make-to-order environment. We propose and compare a constructive heuristic, local search methods, and population-based algorithms. Tests are performed on realistic instances and show that the developed metaheuristics significantly outperform the currently available resolution methods for the same problem.Mon, 22 Jun 2015 11:05:48 +0200A deconstruction-reconstruction metaheuristic for a job scheduling problem : Proceedings of 5th International Conference on Metaheuristics and Nature Inspired Computinghttps://archive-ouverte.unige.ch/unige:45324https://archive-ouverte.unige.ch/unige:45324abstract not availableThu, 15 Jan 2015 14:27:51 +0100Variable Neighborhood Search for a Scheduling Problem with Time Window Penalties : Proceedings of the 14th International Workshop on Project Management and Schedulinghttps://archive-ouverte.unige.ch/unige:45322https://archive-ouverte.unige.ch/unige:45322abstract not availableThu, 15 Jan 2015 14:27:13 +0100Multi-objectives parallel machines scheduling with incompatible jobs : Proceedings of the 15th Annual Congress of the French Operations Research Societyhttps://archive-ouverte.unige.ch/unige:45321https://archive-ouverte.unige.ch/unige:45321abstract not availableThu, 15 Jan 2015 14:26:33 +0100Tabu Search for a Single Machine Scheduling Problem with Discretely Controllable Release Dateshttps://archive-ouverte.unige.ch/unige:40151https://archive-ouverte.unige.ch/unige:40151abstract not availableWed, 10 Sep 2014 14:35:46 +0200Tabu Search for a Preemptive Scheduling Problem with Job Incompatibilitieshttps://archive-ouverte.unige.ch/unige:40150https://archive-ouverte.unige.ch/unige:40150abstract not availableWed, 10 Sep 2014 14:35:08 +0200Tabu Search to Minimize Regular Objective Functions for a Single Machine Scheduling Problem with Rejected Jobs, Setups and Time Windowshttps://archive-ouverte.unige.ch/unige:26480https://archive-ouverte.unige.ch/unige:26480abstract not availableMon, 25 Feb 2013 15:56:52 +0100