18 papers · ranked by Valyu relevance
Mikhail A. Bragin, Emily L. Tucker
Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific disciplines and within areas of strategic importance to society. The MILP problems, however, suffer from combinatorial complexity. Because of integer decision variables, as the problem size increases, the number of possible…
Lara Scavuzzo, Karen Aardal, Andrea Lodi, Neil Yorke-Smith
Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization that offers a powerful modeling language for a wide range of applications. The main engine for solving MILPs is the branch-and-bound algorithm. Adding to the enormous algorithmic progress in MILP solving of the past decades, in more recent…
Daniel Molina-Pérez, Edgar Alfredo Portilla-Flores, Efrén Mezura-Montes, Eduardo Vega-Alvarado + 2 more
'Efrén Mezura-Montes' 'Eduardo Vega-Alvarado' 'María Bárbara Calva-Yañez' 'Thomas Stützle'] Mixed integer nonlinear programming (MINLP) addresses optimization problems that involve continuous and discrete/integer decision variables, as well as nonlinear functions. These problems often exhibit multiple discontinuous…
Vinícius Antonio Battagello, Nei Yoshihiro Soma, Rubens Junqueira Magalhães Afonso, Majid Soleimani-damaneh
'Rubens Junqueira Magalhães Afonso' 'Majid Soleimani-damaneh'] This paper employs a solution to the agent-guidance problem in an environment with obstacles, whose avoidance techniques have been extensively used in the last years. There is still a gap between the solution times required to obtain a trajectory and those…
Duygu Yilmaz Eroglu, Burcu Caglar Gencosman, Fatih Cavdur, H. Cenk Ozmutlu
'H. Cenk Ozmutlu'] In this paper, we analyze a real-world OVRP problem for a production company. Considering real-world constrains, we classify our problem as multicapacitated/heterogeneous fleet/open vehicle routing problem with split deliveries and multiproduct (MCHF/OVRP/SDMP) which is a novel classification of an…
Sayantan Sengupta, Tue Christensen, Gitte Ravn-Haren, Rikke Andersen + 2 more
'Joe Vinson' 'Francesco Visioli'] The dietary vitamin D intake of the Danish population is low, and food fortification is a strategy to increase intake. This paper explores the possibility of vitamin D fortification on the current population food intake in Denmark, such that the population receives adequate amounts of…
Martin Gonzalez, Jose J. López-Espín, Juan Aparicio, El-Ghazali Talbi + 1 more
'El-Ghazali Talbi' 'Nicholas Higham'] Mixed Integer Linear Programs (MILPs) are usually NP-hard mathematical programming problems, which present difficulties to obtain optimal solutions in a reasonable time for large scale models. Nowadays, metaheuristics are one of the potential tools for solving this type of problems…
Albert No
The size of the largest binary single deletion code has been unknown for more than 50 years. It is known that Varshamov-Tenengolts (VT) code is an optimum single deletion code for block length $n\leq10$; however, only a few upper bounds of the size of single deletion code are proposed for larger n. We provide improved…
Xuan Lin
This paper presents a comparative study of data-driven acceleration techniques for mixed-integer bilinear programs (MIBLPs) applied to robot motion planning. MIBLPs combine discrete decision variables and nonlinear constraints, making them computationally challenging for real-time robotics applications. We investigate…
Noah Schulhof, Pattara Sukprasert, Eytan Ruppin, Samir Khuller + 1 more
'Alejandro A. Schäffer'] Integer linear programs (ILPs) and mixed integer programs (MIPs) often have multiple distinct optimal solutions, yet the widely used Gurobi optimization solver returns certain solutions at disproportionately high frequencies. This behavior is disadvantageous, as, in fields such as biomedicine…
Kaihan Fu, Jianjun Liu, Miao Chen, Huiying Zhang + 4 more
'Kai Wen' 'Min Wang' 'Hai Wei'] Flexible job-shop scheduling problems (FJSPs) represent one of the most complex combinatorial optimization challenges. Modern production systems and control processes demand rapid decision-making in scheduling. To address this challenge, we propose a quantum computing approach for…
Xiang Li, Mohammad Reza Bonyadi, Zbigniew Michalewicz, Luigi Barone
This paper presents a hybrid evolutionary algorithm to deal with the wheat blending problem. The unique constraints of this problem make many existing algorithms fail: either they do not generate acceptable results or they are not able to complete optimization within the required time. The proposed algorithm starts…
Rafael Muñoz-Sánchez, Iris Martínez-Salazar, José Luis González-Velarde, Yasmín Á. Ríos Solís + 1 more
'José Luis González-Velarde' 'Yasmín Á. Ríos Solís' 'Mazyar Ghadiri Nejad'] Two hybrid flow shop scheduling lines must be coordinated to assemble batches of terminated products at their last stage. Each product is thus composed of two jobs, each produced in one of the lines. The set of jobs is to be processed in a…
Elisabeth Gaar, Jon Lee, Ivana Ljubić, Markus Sinnl + 1 more
We study a class of integer bilevel programs with second-order cone constraints at the upper-level and a convex-quadratic objective function and linear constraints at the lower-level. We develop disjunctive cuts (DCs) to separate bilevel-infeasible solutions using a second-order-cone-based cut-generating procedure. We…
David A. Liñán, Luis A. Ricardez-Sandoval
Mixed integer nonlinear programming (MINLP) in chemical engineering originated as a tool for solving optimal process synthesis and design problems. Since then, the application of MINLP has expanded to encompass control and operational decisions that are in line with the arising challenges faced by the industry, e.g.…
Xinyu Liu, Qun Chen, Yong Deng
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network…
Zhi-Cheng Wang, Xiao-Bei Wu
Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark…
Maciej Nowak, Tadeusz Trzaskalik, Sebastian Sitarz, Ewa Roszkowska + 1 more
'Marek Szopa'] A problem that appears in many decision models is that of the simultaneous occurrence of deterministic, stochastic, and fuzzy values in the set of multidimensional evaluations. Such problems will be called mixed problems. They lead to the formulation of optimization problems in ordered structures and…