Phex: a computational tool for plate heat exchanges design problems

This paper presents a computational tool (PHEx) developed in Excel VBA for solving sizing and rating design problems involving Chevron type plate heat exchangers (PHE) with 1-pass-1-pass configuration. The rating methodology procedure used in the program is outlined, and a case study is presented with the purpose to show how the program can be used to develop sensitivity analysis to several dimensional parameters of PHE and to observe their effect on transferred heat and pressure drop.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

Special report of the medical division on teletherapy design problems: Cs¹³⁷ /

AEC Report No. TID-5086 (1st REV).

Algorithms for network design and routing problems

In this thesis we study three combinatorial optimization problems belonging to the classes of Network Design and Vehicle Routing problems that are strongly linked in the context of the design and management of transportation networks: the Non-Bifurcated Capacitated Network Design Problem (NBP), the Period Vehicle Routing Problem (PVRP) and the Pickup and Delivery Problem with Time Windows (PDPTW). These problems are NP-hard and contain as special cases some well known difficult problems such as the Traveling Salesman Problem and the Steiner Tree Problem. Moreover, they model the core structure of many practical problems arising in logistics and telecommunications. The NBP is the problem of designing the optimum network to satisfy a given set of traffic demands. Given a set of nodes, a set of potential links and a set of point-to-point demands called commodities, the objective is to select the links to install and dimension their capacities so that all the demands can be routed between their respective endpoints, and the sum of link fixed costs and commodity routing costs is minimized. The problem is called non- bifurcated because the solution network must allow each demand to follow a single path, i.e., the flow of each demand cannot be splitted. Although this is the case in many real applications, the NBP has received significantly less attention in the literature than other capacitated network design problems that allow bifurcation. We describe an exact algorithm for the NBP that is based on solving by an integer programming solver a formulation of the problem strengthened by simple valid inequalities and four new heuristic algorithms. One of these heuristics is an adaptive memory metaheuristic, based on partial enumeration, that could be applied to a wider class of structured combinatorial optimization problems. In the PVRP a fleet of vehicles of identical capacity must be used to service a set of customers over a planning period of several days. Each customer specifies a service frequency, a set of allowable day-combinations and a quantity of product that the customer must receive every time he is visited. For example, a customer may require to be visited twice during a 5-day period imposing that these visits take place on Monday-Thursday or Monday-Friday or Tuesday-Friday. The problem consists in simultaneously assigning a day- combination to each customer and in designing the vehicle routes for each day so that each customer is visited the required number of times, the number of routes on each day does not exceed the number of vehicles available, and the total cost of the routes over the period is minimized. We also consider a tactical variant of this problem, called Tactical Planning Vehicle Routing Problem, where customers require to be visited on a specific day of the period but a penalty cost, called service cost, can be paid to postpone the visit to a later day than that required. At our knowledge all the algorithms proposed in the literature for the PVRP are heuristics. In this thesis we present for the first time an exact algorithm for the PVRP that is based on different relaxations of a set partitioning-like formulation. The effectiveness of the proposed algorithm is tested on a set of instances from the literature and on a new set of instances. Finally, the PDPTW is to service a set of transportation requests using a fleet of identical vehicles of limited capacity located at a central depot. Each request specifies a pickup location and a delivery location and requires that a given quantity of load is transported from the pickup location to the delivery location. Moreover, each location can be visited only within an associated time window. Each vehicle can perform at most one route and the problem is to satisfy all the requests using the available vehicles so that each request is serviced by a single vehicle, the load on each vehicle does not exceed the capacity, and all locations are visited according to their time window. We formulate the PDPTW as a set partitioning-like problem with additional cuts and we propose an exact algorithm based on different relaxations of the mathematical formulation and a branch-and-cut-and-price algorithm. The new algorithm is tested on two classes of problems from the literature and compared with a recent branch-and-cut-and-price algorithm from the literature.

Theory manual to OctVCE – a cartesian cell CFD code with special application to blast wave problems, Department of Mechanical Engineering Report 2007/12

OctVCE is a cartesian cell CFD code produced especially for numerical simulations of shock and blast wave interactions with complex geometries, in particular, from explosions. Virtual Cell Embedding (VCE) was chosen as its cartesian cell kernel for its simplicity and sufficiency for practical engineering design problems. The code uses a finite-volume formulation of the unsteady Euler equations with a second order explicit Runge-Kutta Godonov (MUSCL) scheme. Gradients are calculated using a least-squares method with a minmod limiter. Flux solvers used are AUSM, AUSMDV and EFM. No fluid-structure coupling or chemical reactions are allowed, but gas models can be perfect gas and JWL or JWLB for the explosive products. This report also describes the code’s ‘octree’ mesh adaptive capability and point-inclusion query procedures for the VCE geometry engine. Finally, some space will also be devoted to describing code parallelization using the shared-memory OpenMP paradigm. The user manual to the code is to be found in the companion report 2007/13.

Lattice-dome design using a knowledge-based system approach

In the design of lattice domes, design engineers need expertise in areas such as configuration processing, nonlinear analysis, and optimization. These are extensive numerical, iterative, and lime-consuming processes that are prone to error without an integrated design tool. This article presents the application of a knowledge-based system in solving lattice-dome design problems. An operational prototype knowledge-based system, LADOME, has been developed by employing the combined knowledge representation approach, which uses rules, procedural methods, and an object-oriented blackboard concept. The system's objective is to assist engineers in lattice-dome design by integrating all design tasks into a single computer-aided environment with implementation of the knowledge-based system approach. For system verification, results from design examples are presented.

Mathematical methods for spatially cohesive reserve design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.

Solution Methods for Service Network Design with Resource Management Consideration

La gestion des ressources, équipements, équipes de travail, et autres, devrait être prise en compte lors de la conception de tout plan réalisable pour le problème de conception de réseaux de services. Cependant, les travaux de recherche portant sur la gestion des ressources et la conception de réseaux de services restent limités. La présente thèse a pour objectif de combler cette lacune en faisant l’examen de problèmes de conception de réseaux de services prenant en compte la gestion des ressources. Pour ce faire, cette thèse se décline en trois études portant sur la conception de réseaux. La première étude considère le problème de capacitated multi-commodity fixed cost network design with design-balance constraints(DBCMND). La structure multi-produits avec capacité sur les arcs du DBCMND, de même que ses contraintes design-balance, font qu’il apparaît comme sous-problème dans de nombreux problèmes reliés à la conception de réseaux de services, d’où l’intérêt d’étudier le DBCMND dans le contexte de cette thèse. Nous proposons une nouvelle approche pour résoudre ce problème combinant la recherche tabou, la recomposition de chemin, et une procédure d’intensification de la recherche dans une région particulière de l’espace de solutions. Dans un premier temps la recherche tabou identifie de bonnes solutions réalisables. Ensuite la recomposition de chemin est utilisée pour augmenter le nombre de solutions réalisables. Les solutions trouvées par ces deux méta-heuristiques permettent d’identifier un sous-ensemble d’arcs qui ont de bonnes chances d’avoir un statut ouvert ou fermé dans une solution optimale. Le statut de ces arcs est alors fixé selon la valeur qui prédomine dans les solutions trouvées préalablement. Enfin, nous utilisons la puissance d’un solveur de programmation mixte en nombres entiers pour intensifier la recherche sur le problème restreint par le statut fixé ouvert/fermé de certains arcs. Les tests montrent que cette approche est capable de trouver de bonnes solutions aux problèmes de grandes tailles dans des temps raisonnables. Cette recherche est publiée dans la revue scientifique Journal of heuristics. La deuxième étude introduit la gestion des ressources au niveau de la conception de réseaux de services en prenant en compte explicitement le nombre fini de véhicules utilisés à chaque terminal pour le transport de produits. Une approche de solution faisant appel au slope-scaling, la génération de colonnes et des heuristiques basées sur une formulation en cycles est ainsi proposée. La génération de colonnes résout une relaxation linéaire du problème de conception de réseaux, générant des colonnes qui sont ensuite utilisées par le slope-scaling. Le slope-scaling résout une approximation linéaire du problème de conception de réseaux, d’où l’utilisation d’une heuristique pour convertir les solutions obtenues par le slope-scaling en solutions réalisables pour le problème original. L’algorithme se termine avec une procédure de perturbation qui améliore les solutions réalisables. Les tests montrent que l’algorithme proposé est capable de trouver de bonnes solutions au problème de conception de réseaux de services avec un nombre fixe des ressources à chaque terminal. Les résultats de cette recherche seront publiés dans la revue scientifique Transportation Science. La troisième étude élargie nos considérations sur la gestion des ressources en prenant en compte l’achat ou la location de nouvelles ressources de même que le repositionnement de ressources existantes. Nous faisons les hypothèses suivantes: une unité de ressource est nécessaire pour faire fonctionner un service, chaque ressource doit retourner à son terminal d’origine, il existe un nombre fixe de ressources à chaque terminal, et la longueur du circuit des ressources est limitée. Nous considérons les alternatives suivantes dans la gestion des ressources: 1) repositionnement de ressources entre les terminaux pour tenir compte des changements de la demande, 2) achat et/ou location de nouvelles ressources et leur distribution à différents terminaux, 3) externalisation de certains services. Nous présentons une formulation intégrée combinant les décisions reliées à la gestion des ressources avec les décisions reliées à la conception des réseaux de services. Nous présentons également une méthode de résolution matheuristique combinant le slope-scaling et la génération de colonnes. Nous discutons des performances de cette méthode de résolution, et nous faisons une analyse de l’impact de différentes décisions de gestion des ressources dans le contexte de la conception de réseaux de services. Cette étude sera présentée au XII International Symposium On Locational Decision, en conjonction avec XXI Meeting of EURO Working Group on Locational Analysis, Naples/Capri (Italy), 2014. En résumé, trois études différentes sont considérées dans la présente thèse. La première porte sur une nouvelle méthode de solution pour le "capacitated multi-commodity fixed cost network design with design-balance constraints". Nous y proposons une matheuristique comprenant la recherche tabou, la recomposition de chemin, et l’optimisation exacte. Dans la deuxième étude, nous présentons un nouveau modèle de conception de réseaux de services prenant en compte un nombre fini de ressources à chaque terminal. Nous y proposons une matheuristique avancée basée sur la formulation en cycles comprenant le slope-scaling, la génération de colonnes, des heuristiques et l’optimisation exacte. Enfin, nous étudions l’allocation des ressources dans la conception de réseaux de services en introduisant des formulations qui modèlent le repositionnement, l’acquisition et la location de ressources, et l’externalisation de certains services. À cet égard, un cadre de solution slope-scaling développé à partir d’une formulation en cycles est proposé. Ce dernier comporte la génération de colonnes et une heuristique. Les méthodes proposées dans ces trois études ont montré leur capacité à trouver de bonnes solutions.

Advanced global optimisation for mission analysis and design

This report describes the analysis and development of novel tools for the global optimisation of relevant mission design problems. A taxonomy was created for mission design problems, and an empirical analysis of their optimisational complexity performed - it was demonstrated that the use of global optimisation was necessary on most classes and informed the selection of appropriate global algorithms. The selected algorithms were then applied to the di®erent problem classes: Di®erential Evolution was found to be the most e±cient. Considering the speci¯c problem of multiple gravity assist trajectory design, a search space pruning algorithm was developed that displays both polynomial time and space complexity. Empirically, this was shown to typically achieve search space reductions of greater than six orders of magnitude, thus reducing signi¯cantly the complexity of the subsequent optimisation. The algorithm was fully implemented in a software package that allows simple visualisation of high-dimensional search spaces, and e®ective optimisation over the reduced search bounds.

Striving for inclusive design in the built environment: learning strategy adopted by policy implementers at local authorities in England

The research will explore views on inclusive design policy implementation and learning strategy used in practice by Local Authorities’ planning, building control and policy departments in England. It reports emerging research findings. The research aim was developed from an extensive literature review, and informed by a pilot study with relevant Local Authority departments. The pilot study highlighted gaps within the process of policy implementation, a lack of awareness of the process and flaws in the design guidance policy. This has helped inform the development of a robust research design using both a survey and semi-structured interviews. The questionnaire targeted key employees within Local Authorities designed to establish how employees learn about inclusive design policy and to determine their views on current approaches of inclusive design policy implementation adopted by their Local Authorities. The questionnaire produces 117 responses. Interestingly approximately 9 out of 129 Local Authorities approached claimed that they were unable to participate either because an inclusive design policy was not adopted or they were faced with a high workload and thus unable to take part. An emerging finding is a lack of understanding of inclusive design problems, which may lead to problem with inclusive design policy implementation, and thus adversely affect how the built environment can be experienced. There is a strong indication from the survey respondents indicating that they are most likely to learn about inclusive design from policy guides produced by their Local Authorities and from their colleagues.

Design patterns for promoting peer interaction in discussion forums in MOOCs

Design patterns are a way of sharing evidence-based solutions to educational design problems. The design patterns presented in this paper were produced through a series of workshops, which aimed to identify Massive Open Online Course (MOOC) design principles from workshop participants’ experiences of designing, teaching and learning on these courses. MOOCs present a challenge for the existing pedagogy of online learning, particularly as it relates to promoting peer interaction and discussion. MOOC cohort sizes, participation patterns and diversity of learners mean that discussions can remain superficial, become difficult to navigate, or never develop beyond isolated posts. In addition, MOOC platforms may not provide sufficient tools to support moderation. This paper draws on four case studies of designing and teaching on a range of MOOCs presenting seven design narratives relating to the experience in these MOOCs. Evidence presented in the narratives is abstracted in the form of three design patterns created through a collaborative process using techniques similar to those used in collective autoethnography. The patterns: “Special Interest Discussions”, “Celebrity Touch” and “Look and Engage”, draw together shared lessons and present possible solutions to the problem of creating, managing and facilitating meaningful discussion in MOOCs through the careful use of staged learning activities and facilitation strategies.

Benders, metric and cutset inequalities for multicommodity capacitated network design

Solving multicommodity capacitated network design problems is a hard task that requires the use of several strategies like relaxing some constraints and strengthening the model with valid inequalities. In this paper, we compare three sets of inequalities that have been widely used in this context: Benders, metric and cutset inequalities. We show that Benders inequalities associated to extreme rays are metric inequalities. We also show how to strengthen Benders inequalities associated to non-extreme rays to obtain metric inequalities. We show that cutset inequalities are Benders inequalities, but not necessarily metric inequalities. We give a necessary and sufficient condition for a cutset inequality to be a metric inequality. Computational experiments show the effectiveness of strengthening Benders and cutset inequalities to obtain metric inequalities.

Approximating a class of combinatorial problems with rational objective function

In the late seventies, Megiddo proposed a way to use an algorithm for the problem of minimizing a linear function a(0) + a(1)x(1) + ... + a(n)x(n) subject to certain constraints to solve the problem of minimizing a rational function of the form (a(0) + a(1)x(1) + ... + a(n)x(n))/(b(0) + b(1)x(1) + ... + b(n)x(n)) subject to the same set of constraints, assuming that the denominator is always positive. Using a rather strong assumption, Hashizume et al. extended Megiddo`s result to include approximation algorithms. Their assumption essentially asks for the existence of good approximation algorithms for optimization problems with possibly negative coefficients in the (linear) objective function, which is rather unusual for most combinatorial problems. In this paper, we present an alternative extension of Megiddo`s result for approximations that avoids this issue and applies to a large class of optimization problems. Specifically, we show that, if there is an alpha-approximation for the problem of minimizing a nonnegative linear function subject to constraints satisfying a certain increasing property then there is an alpha-approximation (1 1/alpha-approximation) for the problem of minimizing (maximizing) a nonnegative rational function subject to the same constraints. Our framework applies to covering problems and network design problems, among others.