Models for Bundle Trading in Financial Markets

Bundle trading is a new trend in financial markets that allows traders to submit consolidated orders to sell and buy packages of assets. We propose a new formulation for portfolio bundle trading that extends the previous models of the literature through a more detailed representation of portfolios and the formulation of new bidding requirements. We also present post-optimality tie-breaking procedures intended to discriminate equivalent orders on the basis of their submission times. Numerical results evaluate the "bundle" effect as well as the bidding flexibility and the computational complexity of our formulation. Une nouvelle tendance dans les marchés financiers consiste à transiger des valeurs financières sous forme d'ordres composites d'achat et de vente. Nous proposons une nouvelle formulation basée sur les ordres composites du problème d'allocation de valeurs financières. Notre modèle, comparativement à ceux de la littérature, permet une représentation plus détaillée des portefeuilles financiers et la formulation de nouvelles contraintes transactionnelles. Nous présentons en outre une procédure de discrimination d'ordres équivalents sur la base de leur temps de soumission. Les résultats numériques de notre étude permettent d'évaluer empiriquement l'effet « ordres composites », ainsi que la flexibilité et la complexité numérique de notre formulation.Auction Design, Financial Markets, Bundle Trading, Discrimination Procedures, Mécanisme d'enchères, marchés financiers, ordres composites, procédures de discrimination

Design for Optimized Multi-Lateral Multi-Commodity Markets

In this paper, we propose a design for an an economically efficient, optimized, centralized, multi-lateral, periodic commodity market that addresses explicitly three issues: (i) substantial transportation costs between sellers and buyers; (ii) non homogeneous, in quality and nature, commodities; (iii) complementary commodities that have to be traded simultaneously. The model allows sellers to offer their commodities in lots and buyers to explicitly quantify the differences in quality of the goods produced by each individual seller. The model does not presume that products must be shipped through a market hub. We also propose a multi-round auction that enables the implementation of the direct optimized market and approximates the behaviour of the "ideal" direct optimized mechanism. The process allows buyers and sellers to modify their initial bids, including the technological constraints. The proposed market designs are particularly relevant for industries related to natural resources. We present the models and algorithms required to implement the optimized market mechanisms, describe the operations of the multi-round auction, and discuss applications and perspectives. Nous présentons un concept de marché optimisé, centralisé, multilatéral et périodique pour l'acquisition de produits qui traite explicitement les trois aspects suivants: (i) des coûts de transport importants des vendeurs vers les acheteurs; (ii) des produits non homogènes en valeur et qualité; des complémentarités entre les divers produits qui doivent donc être négociés simultanément. Le modèle permet aux vendeurs d'offrir leurs produits groupés en lots et aux acheteurs de quantifier explicitement leur évaluation des lots mis sur le marché par chaque vendeur. Le modèle ne suppose pas que les produits doivent être expédiés par un centre avant d'être livrés. Nous proposons également un mécanisme de tâtonnement à rondes multiples qui approxime le comportement du marché direct optimisé et qui permet de mettre ce dernier en oeuvre. Le processus de tâtonnement permet aux vendeurs et aux acheteurs de modifier leurs mises initiales, incluant les contraintes technologiques. Les concepts proposés sont particulièrement adaptés aux industries reliées aux matières premières. Nous présentons les modèles et algorithmes requis à la mise en oeuvre du marché multi-latéral optimisé, nous décrivons le fonctionnement du processus de tâtonnement, et nous discutons les applications et perspectives reliées à ces mécanismes de marché.Market design, optimized multi-lateral multi-commodity markets, multi-round auctions, Design de marché, marché multi-latéraux optimisés, processus de tâtonnement

Finding Best Compiler Options for Critical Software Using Parallel Algorithms

The efficiency of a software piece is a key factor for many systems. Real-time programs, critical software, device drivers, kernel OS functions and many other software pieces which are executed thousands or even millions of times per day require a very efficient execution. How this software is built can significantly affect the run time for these programs, since the context is that of compile-once/run-many. In this sense, the optimization flags used during the compilation time are a crucial element for this goal and they could make a big difference in the final execution time. In this paper, we use parallel metaheuristic techniques to automatically decide which optimization flags should be activated during the compilation on a set of benchmarking programs. The using the appropriate flag configuration is a complex combinatorial problem, but our approach is able to adapt the flag tuning to the characteristics of the software, improving the final run times with respect to other spread practicesThis research has been partially funded by the Spanish MINECO and FEDER projects (TIN2014-57341-R (http://moveon.lcc.uma.es), TIN2016-81766-REDT (http://cirti.es), and TIN2017-88213-R (http://6city.lcc.uma.es). It is also funded by Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Two-Echelon Vehicle Routing Problem: A Satellite Location Analysis

Tech. Rep. CIRRELT-2009-15, CIRRELT, Montrea

Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and "grey Zone" customers arising in urban logistics

We present a multi-objective two-echelon vehicle routing problem with vehicle synchronization and "grey zone" customers arising in the context of urban freight deliveries. Inner-city center deliveries are performed by small vehicles due to access restrictions, while deliveries outside this area are carried out by conventional vehicles for economic reasons. Goods are transferred from the first to the second echelon by synchronized meetings between vehicles of the respective echelons. We investigate the assignment of customers to vehicles, i.e., to the first or second echelon, within a so-called "grey Zone" on the border of the inner city and the area around it. While doing this, the economic objective as well as negative external effects of transport, such as emissions and disturbance (negative impact on citizens due to noise and congestion), are taken into account to include objectives of companies as well as of citizens and municipal authorities. Our metaheuristic - a large neighborhood search embedded in a heuristic rectangle/cuboid splitting - addresses this problem efficiently. We investigate the impact of the free assignment of part of the customers ("grey Zone") to echelons and of three different city layouts on the solution. Computational results show that the impact of a "grey Zone" and thus the assignment of these customers to echelons depend significantly on the layout of a city. Potentially pareto-optimal solutions for two and three objectives are illustrated to efficiently support decision makers in sustainable city logistics planning processes

A cooperative parallel metaheuristic for the capacitated vehicle routing problem

This paper introduces a cooperative parallel metaheuristic for the capacitated vehicle routing problem. The proposed metaheuristic consists of multiple parallel tabu search threads that cooperate by asynchronously exchanging best-found solutions through a common solution pool. The solutions sent to the pool are clustered according to their similarities. The search history information identified from the solution clusters is applied to guide the intensification or diversification of the tabu search threads. Computational experiments on two sets of large-scale benchmark instance sets from the literature demonstrate that the suggested metaheuristic is highly competitive, providing new best solutions to ten of those well-studied instances.acceptedVersio

A Parallel multi-neighborhood cooperative tabu search for capacitated vehicle routing problems

This paper presents a parallel tabu search algorithm that utilizes several different neighborhood structures for solving the capacitated vehicle routing problem. Single neighborhood or neighborhood combinations are encapsulated in tabu search threads and they cooperate through a solution pool for the purpose of exploiting their joint power. The computational experiments on 32 large scale benchmark instances show that the proposed method is highly effective and competitive, providing new best solutions to four instances while the average deviation of all best solutions found from the collective best results reported in the literature is about 0.22%. We are also able to associate the beneficial use of special neighborhoods with some test instance characteristics and uncover some sources of the collective power of multi-neighborhood cooperation.acceptedVersio

Capacity Planning with Uncertainty on Contract Fulfillment

This paper focuses on the tactical planning problem faced by a shipper which seeks to secure transportation and warehousing capacity, such as containers, vehicles or space in a warehouse, of different sizes, costs, and characteristics, from a carrier or logistics provider, while facing different sources of uncertainty. The uncertainty can be related to the loads to be transported or stored, the cost and availability of ad-hoc capacity on the spot market in the future, and the availability of the contracted capacity in the future when the shipper needs it. This last source of uncertainty on the capacity loss on the contracted capacity is particularly important in both long-haul transportation and urban distribution applications, but no optimization methodology has been proposed so far. We introduce the Stochastic Variable Cost and Size Bin Packing with Capacity Loss problem and model that directly address this issue, together with a metaheuristic to efficiently address it. We perform a set of extensive numerical experiments on instances related to long-haul transportation and urban distribution contexts and derive managerial insights on how such capacity planning should be performed

Extreme-Point-based Heuristics for the Three-Dimensional Bin Packing problem

One of the main issues in addressing three-dimensional packing problems is finding an efficient and accurate definition of the points at which to place the items inside the bins, because the performance of exact and heuristic solution methods is actually strongly influenced by the choice of a placement rule. We introduce the extreme point concept and present a new extreme point-based rule for packing items inside a three-dimensional container. The extreme point rule is independent from the particular packing problem addressed and can handle additional constraints, such as fixing the position of the items. The new extreme point rule is also used to derive new constructive heuristics for the three-dimensional bin-packing problem. Extensive computational results show the effectiveness of the new heuristics compared to state-of-the-art results. Moreover, the same heuristics, when applied to the two-dimensional bin-packing problem, outperform those specifically designed for the proble

Designing the master schedule for demand-adaptive transit systems

Abstract Demand-Adaptive Systems (DAS) display features of both traditional fixed-line bus services and purely on-demand systems such as dial-a-ride, that is they offer demand-responsive services within the framework of traditional scheduled bus transportation. A DAS bus line serves, on one hand, a given set of compulsory stops according to a predefined schedule specifying the time windows associated with each, providing the traditional use of the transit line, without requiring any reservation. On the other hand, passengers may also issue requests for transportation between two desired, optional, stops, which induces detours in the vehicle routes. The design of a DAS line is a complex planning operation that requires to determine not only its design in terms of selecting the compulsory stops, but also its master schedule in terms of the time windows associated with the compulsory stops. Designing a DAS thus combines elements of strategic and tactical planning. In this paper we focus on determining a master-schedule for a single DAS line. We propose a mathematical description and a solution framework based on the estimation of a number of statistical parameters of the demand and the DAS line service. Results of numerical experiments are also given and analyzed