J.P.M. Gonçalves

Heuristics for convex mixed integer nonlinear programs

In this paper, we describe the implementation of some heuristics for convex mixed integer nonlinear programs. The work focuses on three families of heuristics that have been successfully used for mixed integer linear programs: diving heuristics, the Feasibility Pump, and Relaxation Induced Neighborhood Search (RINS). We show how these heuristics can be adapted in the context of mixed integer nonlinear programming. We present results from computational experiments on a set of instances that show how the heuristics implemented help finding feasible solutions faster than the traditional branch-and-bound algorithm and how they help in reducing the total solution time of the branch-and-bound algorithm.

Mixed-Mode Cohesive Damage Model Applied to the Simulation of the Mechanical Behaviour of Laminated Composite Adhesive Joints

A study of the mechanical behaviour of laminated composite adhesive joints is presented in this paper. The study consists of both numerical simulations and experimental tests. It concentrates on single lap-shear joints made of carbon–epoxy laminated composites and an epoxy adhesive. The main objective is to verify the adequacy of cohesive damage models for the strength prediction of bonded joints. These models are attractive in modelling fracture problems since they do not require the definition of an initial crack and they model damage propagation without any user intervention. A mixed-mode cohesive damage model is used to simulate damage onset and growth in the adhesive layer. The model is an extension of pure mode (I and II) trapezoidal cohesive damage models. The trapezoidal shape in the constitutive law is more valid when ductile adhesives are used. The mixed-mode model requires a complete characterization of the cohesive parameters in pure modes, determined with an inverse method. Tensile tests are performed for joints with different overlap lengths. It is shown that the numerical simulations represent with a reasonable accuracy the mechanical behaviour of the joints tested.

A family of linear programming algorithms based on an algorithm by von Neumann

In this article, we present a family of algorithms for linear programming based on an algorithm proposed by von Neumann. The von Neumann algorithm is very attractive due to its simplicity, but is not practical for solving most linear programs to optimality due to its slow convergence. Our algorithms were developed with the objective of improving the practical convergence of the von Neumann algorithm while maintaining its attractive features. We present results from computational experiments on a set of linear programming problems that show significant improvements over the von Neumann algorithm.

Numerical and experimental analyses of composite bonded double-strap repairs under high-cycle fatigue

ABSTRACT This work addresses the behaviour of double-strap repairs of carbon-epoxy laminates under high-cycle fatigue loading. Experimental static and fatigue three-point bending tests were performed considering simpler double-strap bonded joints. Numerical analyses involving a cohesive mixed-mode I+II zone model appropriate for high-cycle fatigue loading considering quasi-static and fatigue degradation in a sole damage parameter were accomplished. The numerical fatigue life prediction and normalised compliance versus number of cycles curve are in close agreement with the experimental results. The numerical model was subsequently used to assess the influence of ±5% variation of several parameters intrinsic to fatigue behaviour on the numerically obtained fatigue lives. It was concluded that the exponent parameter of the modified Paris law is the most influent one. In addition, it was concluded that a concurrent variation of ±5% of all analysed parameters can explain the experimental scatter obtained.

Simulation based analytics for efficient planning and management in multimodal freight transportation industry

The multimodal freight transportation planning is a complex problem with several factors affecting decisions, including network coverage, carriers and their schedules, existing contractual agreements with carriers and clients, carrier capacity constraints, and market conditions. Day-to-day operations like booking and bidding are mostly done manually and there is a lack of decision support tools to aid the operators. These operations are governed by a complex set of business rules involving service agreements with the clients, contractual agreements with the carriers and forwarders own business objectives. The multimodal freight transportation industry lacks a comprehensive solution for end-to-end route optimization and planning. We developed analytics for trade lane managers to identify and exploit opportunities to improve procurement, carrier selection, capacity planning, and business rules management. Our simulation based analytics tool is useful for managing business rules and for doing what-if analysis which can lead to better resource planning, cost management, and rate negotiations.