Modeling of Biological Intelligence for SCM System Optimization

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms

Internet of Things (IoT) Utilization to Improve Performance and Productivity of Internal Supply Chain

The inevitable transformations brought about by the rapidly changing Internet of Things (IoT) impact all aspects of life today, including management and businesses. Specifically, areas of businesses depending mainly on internal supply chain capacity are experiencing a paradigm shift to ensure effective company performance regarding purchases, production, company sales, and product distribution. This shift means that challenges faced by the internal chain supply unit can be solved by adopting and adapting IoT as a new way to minimize work delays and save time. Moreover, IoT automatically leads to performance and productivity increases. Therefore, the present paper aims to justify adopting and adapting IoT applications in Indonesian companies, including retail businesses. Most companies’ internal supply chain units face several difficulties during and after the devastating peak of COVID-19, which has led to a total global lockdown. These problems' complexity is exponential and requires innovative ways to solve their prevailing challenges. This study used observation, interview, and documentary research methods through a large-scale survey. The survey obtained the necessary information regarding how companies utilize IoT to improve their performance and productivity without hindering their internal supply chain and production units. The study concluded that the adoption of IoT, if well implemented, leads to a sustainable company and uninterrupted supply chain performance, indicating the proper performance of the organization. Doi: 10.28991/esj-2021-SP1-017 Full Text: PD

Routing Applications in Newspaper Delivery

-The goal of this report is to give an up-to-date account of routing applications in the newspaper business. We describe the newspaper supply chain, and focus on the “last mile” distribution that has been advocated as an application of arc routing in the literature. A literature survey is provided, followed by a discussion of the arc routing model and its adequacy to newspaper applications. A more general and normally more adequate model: The Node, Edge, and Arc Routing Problem, is discussed. Characteristics of routing problems in carrier delivery are presented, together with a case study from the development of a web-based route design and revision system. Finally, summary, conclusions, and prospects for the future are given

Optimizing routes using the vehicle routing problem

With the emergence of e-commerce and its significant growth during the COVID-19 pandemic, more people aim to ship their products as fast as possible. More organizations such as DHL and USPS invest vast amounts of money in minimizing transportation costs while finding the shortest route that the delivery man should take to reach different destinations. My Work Project will evolve around studying the Vehicle Routing Problem that uses different algorithms to find the shortest route depending on various constraints. This project will include four parts: a literature review expressing an overview of the vehicle routing issue; then a state of the art of algorithm to understand the meaning behind the main algorithms. Finally, build a code (coding platform) using the algorithms discussed previously to solve a situation for the traveling salesman person and VRP

Optimized cross-organizational business process monitoring: Design and enactment

Organizations can implement the agility required to survive in the rapidly evolving business landscape by focusing on their core business and engaging in collaborations with other partners. This entails the need for organizations to monitor the behavior of the partners with which they collaborate. The design and enactment of monitoring, in this scenario, must become flexible and adapt as the collaboration evolves. We propose an approach to flexibly design and enact cross-organizational business process monitoring based on Product-Based Workflow Design. Our approach allows organizations to capture monitoring requirements, optimize such requirements, e.g. choosing the monitoring process with lowest cost or highest availability, and enacting the optimal monitoring process through a service-oriented approach. Optimization, in particular, is made efficient by adopting an Ant-colony optimization heuristic. The paper also describes a prototypical implementation of our approach in the ProM framework

A robust solving strategy for the vehicle routing problem with multiple depots and multiple objectives

This document presents the development of a robust solving strategy for the Vehicle Routing Problem with Multiple Depots and Multiple Objectives (MO-MDVRP). The problem tackeled in this work is the problem to minimize the total cost and the load imbalance in vehicle routing plan for distribution of goods. This thesis presents a MILP mathematical model and a solution strategy based on a Hybrid Multi- Objective Scatter Search Algorithm. Several experiments using simulated instances were run proving that the proposed method is quite robust, this is shown in execution times (less than 4 minutes for an instance with 8 depots and 300 customers); also, the proposed method showed good results compared to the results found with the MILP model for small instances (up to 20 clients and 2 depots).MaestríaMagister en Ingeniería Industria

ALTERNATE MODELS FOR NATURAL GAS TRANSPORTATION SYSTEM PERFORMANCE OPTIMIZATION

The Natural Gas market in the U.S is growing rapidly with evidence that the nation has enough shale reserves to power the country for the next century. To ensure continued economic benefits through the use of this environmentally desired energy source, it becomes important to optimize the transportation network system design. Transportation through pipelines is one of the most common methods used to distribute Natural Gas from source to destination. This transportation system, consisting of pipelines, compressors and other supporting equipment, must be optimized, considering all relevant parameters to minimize cost and increase profit. The research presented here improves on the fuel cost minimization models in literature to incorporate pipeline elevation and safety requirements. A new model is proposed to consider the entire transportation network as a single system and optimize it considering all relevant parameters. The optimization model is setup as a mixed integer nonlinear program. The proposed model is used to optimize the pipeline network for a case study, evaluate the model as well as investigate design capacity and installed capacity of pipeline network

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner

Meta-heuristic based Construction Supply Chain Modelling and Optimization

Driven by the severe competition within the construction industry, the necessity of improving and optimizing the performance of construction supply chain has been aroused. This thesis proposes three problems with regard to the construction supply chain optimization from three perspectives, namely, deterministic single objective optimization, stochastic optimization and multi-objective optimization respectively. Mathematical models for each problem are constructed accordingly and meta-heuristic algorithms are developed and applied for resolving these three problems