Automated System for Freight Transportation Optimization on the Transport Network

An automated system for freight traffic optimization on a transport network has been developed, which is realized in the form of a complex computer program with application of the visual design environment of Embarcadero RAD Studio. The program complex consists of the main form from which two subprograms are loaded. The search of optimum routes performed by the routing optimization subprogram is used at transportations of freight on the set transport network based on different schemes (from one vertex (the supplier) to all other vertices (consumers), serially – from each vertex to all other vertices, and from two (or several) set of vertices to all other vertices). Freight delivery between the supply and consumption points was optimized by means of the freight transportation optimization subprogram, taking into account the restrictions on the volume of freight at the points of departure and destination

The adaptation of the harmony search algorithm to the ATSP with the evaluation of the influence of the pitch adjustment place on the quality of results

The paper is an extended version of the conference article, which presents a modification of the Harmony Search algorithm, adapted to the effective resolution of the asymmetric case of the Traveling Salesman Problem. The efficacy of the proposed approach was measured with benchmarking tests and in a comparative study based on the results obtained with the Nearest Neighbor Algorithm, Greedy Local Search and Hill Climbing. The discussion also embraced the study of the convergence of the proposed algorithm and the analysis of the impact of the pitch adjustment place on the quality of the solutions

Heuristic methods for the periodic Shipper Lane Selection Problem in transportation auctions

none3siopenTriki, Chefi; Mirmohammadsadeghi, Seyedmehdi; Piya, SujanTriki, Chefi; Mirmohammadsadeghi, Seyedmehdi; Piya, Suja

Three Essays on Game Theory and Computation

The results section of my thesis includes three chapters. The first two chapters are on theoretical game theory. In both chapters, by mathematical modelling and game theoretical tools, I am predicting the behaviour of the players in some real world issues. Hoteling-Downs model plays an important role in the modern political interpretations. The first chapter of this study investigates an extension of Hoteling-Downs model to have multi-dimensional strategy space and asymmetric candidates. Chapter 3 looks into the inspection game where the inspections are not the same in the series of sequential inspections. By modelling the game as a series of recursive zero-sum games I find the optimal strategy of the players in the equilibrium. The forth chapter investigates direct optimization methods for large scale problems. Using Matlab implementations of Genetic and Nelder-Mead algorithms, I compare the efficiency and accuracy of the most famous direct optimization methods for unconstraint optimization problems based on differing number of variables

Emergency Resource Layout with Multiple Objectives under Complex Disaster Scenarios

Effective placement of emergency rescue resources, particularly with joint suppliers in complex disaster scenarios, is crucial for ensuring the reliability, efficiency, and quality of emergency rescue activities. However, limited research has considered the interaction between different disasters and material classification, which are highly vital to the emergency rescue. This study provides a novel and practical framework for reliable strategies of emergency rescue under complex disaster scenarios. The study employs a scenario-based approach to represent complex disasters, such as earthquakes, mudslides, floods, and their interactions. In optimizing the placement of emergency resources, the study considers government-owned suppliers, framework agreement suppliers, and existing suppliers collectively supporting emergency rescue materials. To determine the selection of joint suppliers and their corresponding optimal material quantities under complex disaster scenarios, the research proposes a multi-objective model that integrates cost, fairness, emergency efficiency, and uncertainty into a facility location problem. Finally, the study develops an NSGA-II-XGB algorithm to solve a disaster-prone province example and verify the feasibility and effectiveness of the proposed multi-objective model and solution methods. The results show that the methodology proposed in this paper can greatly reduce emergency costs, rescue time, and the difference between demand and suppliers while maximizing the coverage of rescue resources. More importantly, it can optimize the scale of resources by determining the location and number of materials provided by joint suppliers for various kinds of disasters simultaneously. This research represents a promising step towards making informed configuration decisions in emergency rescue work

Hybrid metaheuristics for solving multi-depot pickup and delivery problems

In today's logistics businesses, increasing petrol prices, fierce competition, dynamic business environments and volume volatility put pressure on logistics service providers (LSPs) or third party logistics providers (3PLs) to be efficient, differentiated, adaptive, and horizontally collaborative in order to survive and remain competitive. In this climate, efficient computerised-decision support tools play an essential role. Especially, for freight transportation, e efficiently solving a Pickup and Delivery Problem (PDP) and its variants by an optimisation engine is the core capability required in making operational planning and decisions. For PDPs, it is required to determine minimum-cost routes to serve a number of requests, each associated with paired pickup and delivery points. A robust solution method for solving PDPs is crucial to the success of implementing decision support tools, which are integrated with Geographic Information System (GIS) and Fleet Telematics so that the flexibility, agility, visibility and transparency are fulfilled. If these tools are effectively implemented, competitive advantage can be gained in the area of cost leadership and service differentiation. In this research, variants of PDPs, which multiple depots or providers are considered, are investigated. These are so called Multi-depot Pickup and Delivery Problems (MDPDPs). To increase geographical coverage, continue growth and encourage horizontal collaboration, efficiently solving the MDPDPs is vital to operational planning and its total costs. This research deals with designing optimisation algorithms for solving a variety of real-world applications. Mixed Integer Linear Programming (MILP) formulations of the MDPDPs are presented. Due to being NP-hard, the computational time for solving by exact methods becomes prohibitive. Several metaheuristics and hybrid metaheuristics are investigated in this thesis. The extensive computational experiments are carried out to demonstrate their speed, preciseness and robustness.Open Acces

Traveling Salesman Problem

This book is a collection of current research in the application of evolutionary algorithms and other optimal algorithms to solving the TSP problem. It brings together researchers with applications in Artificial Immune Systems, Genetic Algorithms, Neural Networks and Differential Evolution Algorithm. Hybrid systems, like Fuzzy Maps, Chaotic Maps and Parallelized TSP are also presented. Most importantly, this book presents both theoretical as well as practical applications of TSP, which will be a vital tool for researchers and graduate entry students in the field of applied Mathematics, Computing Science and Engineering