ILP Approach Research Articles

Optimal recharge sequencing in multi-AGV systems: A mixed ILP approach

Battery level is a critical issue in AGV transportation systems, as AGVs cannot run out of power while operating. Hence, at some point they will be forced to stop and recharge at any of the charging stations available in the warehouse. The question that immediately arises is where, and when, to recharge in an optimal way. Assuming that an AGV has already been assigned a task sequence consisting of visiting a number of working stations, stops at charging stations should be optimally inserted. Here, we do so by minimizing the total tour time, including recharges. Recently, this problem was cast as a mixed integer nonlinear program that also included linear and nonlinear constraints. We recast this problem into a mixed integer linear program under linear constraints, which allows to find an exact solution. Moreover, we derive a procedure to reduce the number of variables of the problem. We also show that, when a charging station is visited, bringing the level of charge to the maximum allowed is optimal except for the case where the tour can be completed without other stops. Finally, we present a stochastic formulation of the problem to consider the presence of multiple AGVs in the layout, which may affect the time spent by AGVs at charging stations due to queuing and, consequently, the optimal solution. Interestingly, the linear formulation of the problem allows to fully characterize the optimal solution as a function of the expected occupancies of the charging stations.

Investigation of home appliances industry and devices obsolescence considering energy consumption

The objective of this study is to optimize a linear objective function that pertains to the obsolescence of home appliances in a household. The approach introduced is an ILP-based method that is both simple and adaptable. This optimization guarantees that the total energy consumption remains below a predetermined energy threshold, while also adhering to an inequality constraint. The proposed methodology was effectively tested using a household containing four home appliances: a washing machine, a dishwasher, a refrigerator, and an oven. The findings indicate that the refrigerator is the most hazardous and inexpensive home appliance. The current formulation aims to optimize the device's lifespan considering the customer's financial constraints and the expenses associated with repairing and replacing its parts. This study centers on the maintenance of printed circuit boards (PCBs) and considers the effects of degradation-related malfunctions, as assessed through testing. Moreover, we employ an additional ILP approach to assess the vulnerability of refrigerator’s PCB components by determining which ones should be replaced when a customer has limited financial resources.

An ILP approach for tactical flight rescheduling during airport access mode disruptions

AbstractAirport access mode disruptions, such as a subway shutdown, threaten the whole passenger door‐to‐door journey. When such a disruptive event occurs, knowledge of passengers' delays would help the airport operation centre to decide if a departure flight should be delayed. This paper proposes a tactical flight rescheduling at an airport to minimise the number of stranded passengers while considering operational constraints. An integer linear programming formulation of the problem is presented. Constraints such as terminal capacities, maximal runway throughput, minimum turnaround time or minimum transfer time for connecting passengers are considered. An exact and heuristic resolution is proposed and compared to a study case around Paris‐Charles de Gaulle airport. The new schedule satisfies the operational constraints and reduces up to 60% of the number of stranded passengers with moderate deviation from the initial planning.

An ILP Approach to Learn MKNF+ Rules for Fault Diagnosis

An ILP Approach to Learn MKNF+ Rules for Fault Diagnosis

An ILP Approach to Determine Smallest 4-Regular Non-Hamiltonian, Nontraceable, and Nonhomogeneously Traceable Graphs

An ILP Approach to Determine Smallest 4-Regular Non-Hamiltonian, Nontraceable, and Nonhomogeneously Traceable Graphs

Computing a Consensus Phylogeny via Leaf Removal.

Given a set [Formula: see text]. of phylogenetic trees with the same leaf-label set X, we wish to remove some leaves from the trees so that there is a tree T with leaf-label set X displaying all the resulting trees. Note that the labels of leaves removed from one input tree may be different from those of leaves removed from another input tree. One objective is to minimize the total number of leaves removed from the trees, whereas the other is to minimize the maximum number of leaves removed from an input tree. Chauve et al. refer to the problem with the first (respectively, second) objective as AST-LR (respectively, AST-LR-d), and they show that both problems are NP-hard, where NP is the class of problems solvable in non-deterministic polynomial time. They further present algorithms for the parameterized versions of both problems. In this article, we point out that their algorithm for the parameterized version of AST-LR is flawed and present a new algorithm. Since neither Chauve et al.'s algorithm for AST-LR-d nor our new algorithm for AST-LR looks practical, we further design integer-linear programming (ILP for short) models for AST-LR and AST-LR-d, and we discuss speedup issues when using popular ILP solvers (say, GUROBI or CPLEX) to solve the models. Our experimental results show that our ILP approach is quite efficient.

Does Relaxing the Infinite Sites Assumption Give Better Tumor Phylogenies? An ILP-Based Comparative Approach.

Most of the evolutionary history reconstruction approaches are based on the infinite sites assumption, which states that mutations appear once in the evolutionary history. The Perfect Phylogeny model is the result of the infinite sites assumption and has been widely used to infer cancer evolution. Nonetheless, recent results show that recurrent and back mutations are present in the evolutionary history of tumors, hence the Perfect Phylogeny model might be too restrictive. We propose an approach that allows losing previously acquired mutations and multiple acquisitions of a character. Moreover, we provide an ILP formulation for the evolutionary tree reconstruction problem. Our formulation allows us to tackle both the Incomplete Directed Phylogeny problem and the Clonal Reconstruction problem when general evolutionary models are considered. The latter problem is fundamental in cancer genomics, the goal is to study the evolutionary history of a tumor considering as input data the fraction of cells having a certain mutation in a set of cancer samples. For the Clonal Reconstruction problem, an experimental analysis shows the advantage of allowing mutation losses. Namely, by analyzing real and simulated datasets, our ILP approach provides a better interpretation of the evolutionary history than a Perfect Phylogeny. The software is at https://github.com/AlgoLab/gppf.

Self-Aligned Double Patterning-Aware Detailed Routing With Double Via Insertion and Via Manufacturability Consideration

In 10nm technology node, self-aligned double patterning (SADP) and triple patterning lithography (TPL) allow us to achieve minimum wiring pitch of around 45nm. While metal layers can be printed by SADP, via layer manufacturing requires TPL to maintain design rules. SADP-aware detailed routing is proposed to ensure decomposability of metal layer patterns. However, its routing solution does not automatically guarantee TPL decomposable via layers. Vias have an inherently low reliability and via failure causes a great yield loss. Double via insertion (DVI) is an effective means to increase yield by reducing via failures. With the restriction of SADP design rules and consideration of TPL decomposability for via layers, DVI becomes a more challenging problem. In this paper, we consider DVI and via layer TPL manufacturability simultaneously in SADP-aware detailed routing. Both spacer-is-metal and spacer-is-dielectric types of SADP are considered. Furthermore, we tackle the TPL-aware DVI in postrouting stage. Both ILP and high-performance heuristic solutions are proposed. The experimental results demonstrate our router can obtain 100% routability and TPL decomposable via layers with reduced dead via count. Meanwhile, compared with the ILP approach to solve TPL-aware DVI problem, the heuristic approach can achieve similar solution quality and significant speedup.

Scheduling of synchronous data flow models onto scratchpad memory-based embedded processors

In this article, we propose a heuristic algorithm for scheduling synchronous data flow (SDF) models on scratch pad memory (SPM) enhanced processors with the objective of minimizing its steady-state execution time. The task involves partitioning the limited on-chip SPM for actor code and data buffer, and executing actors in such a manner that the physical SPM is time shared with different actors and buffers (formally defined as code overlay and data overlay, respectively). In our setup, a traditional minimum buffer schedule could result in very high code overlay overhead and therefore may not be optimal. To reduce the number of direct memory access (DMA) transfers, actors need to be grouped into segments. Prefetching of code and data overlay that overlaps DMA transfers with actor executions also need to be exploited. The efficiency of the our heuristic was evaluated by compiling ten stream applications onto one synergistic processing engine (SPE) of an IBM Cell Broadband Engine. We compare the performance results of our heuristic approach with a minimum buffer scheduling approach and a 3-stage ILP approach, and show that our heuristic is able to generate high quality solutions with fast algorithm run time.

Intelligence-Led Policing As a Framework for Responding to Terrorism

Leading police associations in the United States and the United Kingdom have advocated that law enforcement adopt an intelligence-led policing model (ILP). Much like the situation with community policing, there does not appear to be a commonly accepted definition of ILP nor of the practical implications for police agencies' mission, structure, and processes. This article presents a model of ILP that builds on community policing, problem solving, and continuous improvement business models that have been adopted by police departments. Examples of these practices are reviewed as a method of illustrating the promise of an ILP approach. A broad conceptualization of ILP is presented under the belief that ILP will be most likely integrated into law enforcement and will have the greatest impact if it is adopted from an “all crimes” perspective. The article concludes with illustrations of the utility of ILP for addressing threats of domestic and international terrorism.

An ILP Approach to the Slack Driven Scheduling Problem

With the advent of deep sub-micron era, there is a demand to consider the design closure problem in high-level synthesis. It is well known that the slack is an effective means of tolerating the uncertainties in operation delays. Previous work ever attempted to increase the usable slack based on a given initial schedule. Instead of the post-processing approach, this paper is the first attempt to the simultaneous application of operation scheduling and slack optimization. We use a 0-1 integer linear programming (0-1 ILP) approach to formally formulate the problem. Under the design constraints (timing and resource), our approach is applicable to two different objective functions: the maximization of the total usable slack and the maximization of the number of non-zero slack operations. Compared with previous work, our approach has the following two advantages: first, our approach guarantees the optimality; second, our approach is more suitable for the design space exploration.