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Many academic disciplines - including information systems, computer science, and operations management - face scheduling problems as important decision making tasks. Since many scheduling problems are NP-hard in the strong sense, there is a…
This paper presents a method for choosing a Particle Swarm Optimization based optimizer for the Dynamic Vehicle Routing Problem on the basis of the initially available data of a given problem instance. The optimization algorithm is chosen…
Decision making in the Agriculture domain can be a complex task. The land area allocated to each crop should be fixed every season according to several parameters: prices, demand, harvesting periods, seeds, ground, season etc... The…
This paper considers the problem of scheduling a single batch processing machine such that the total number of tardy jobs is minimized. The machine can simultaneously process several jobs as a batch as long as the machine capacity is not…
This paper addresses the problem of planning successive Space Debris Collecting missions so that they can be achieved at minimal cost by a generic vehicle. The problem mixes combinatorial optimization to select and order the debris among a…
In this paper, the differences between an integrated and hierarchical generation and transmission expansion planning approaches are first described. Then, the hierarchical approach is described in detail. In general terms, in this scheme…
Stochastic sequential decision making often requires hierarchical structure in the problem where each high-level action should be further planned with primitive states and actions. In addition, many real-world applications require a plan…
This paper considers a generalization of the Path Finding (PF) problem with refuelling constraints referred to as the Gas Station Problem (GSP). Similar to PF, given a graph where vertices are gas stations with known fuel prices, and edge…
This paper investigates the use of Multi-Task Bayesian Optimization for tuning decentralized trajectory generation algorithms in multi-drone systems. We treat each task as a trajectory generation scenario defined by a specific number of…
Excessive greenhouse gas emissions from the transportation sector have led companies to move towards a sustainable supply chain network design. In this study we present a new bi-objective non-linear formulation where multiple inventory…
We propose a new event-driven method for on-line trajectory optimization to solve the data harvesting problem: in a two-dimensional mission space, N mobile agents are tasked with the collection of data generated at M stationary sources and…
Large scale-free graphs are famously difficult to process efficiently: the skewed vertex degree distribution makes it difficult to obtain balanced partitioning. Our research instead aims to turn this into an advantage by partitioning the…
Inventory Routing Problem (IRP) is a crucial challenge in supply chain management as it involves optimizing efficient route selection while considering the uncertainty of inventory demand planning. To solve IRPs, usually a two-stage…
General Electric (GE) Gas Power, a leading manufacturer of gas and steam turbines, manufactures and installs these turbines in power generation plants worldwide. They source components for these turbines from suppliers globally and…
The unrestricted block relocation problem is an important optimization problem encountered at terminals, where containers are stored in stacks. It consists in determining the minimum number of container moves so as to empty the considered…
We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the…
Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a hard problem due to the trade- offs between performance and monetary cost. The problem can be further complicated when multiple BoT applications need to be…
Graph stream summarization refers to the process of processing a continuous stream of edges that form a rapidly evolving graph. The primary challenges in handling graph streams include the impracticality of fully storing the ever-growing…
Aerial base stations (ABSs) mounted on unmanned aerial vehicles (UAVs) are capable of extending wireless connectivity to ground users (GUs) across a variety of scenarios. However, it is an NP-hard problem with exponential complexity in $M$…
This paper outlines the ideas behind developing a graph-based heuristic-driven routing algorithm designed for a particular instance of a goods transportation problem with a single good type. The proposed algorithm solves the optimization…