Chris T. Kiranoudis

Dynamic modeling and control of supply chain systems: A review

Supply chains are complicated dynamical systems triggered by customer demands. Proper selection of equipment, machinery, buildings and transportation fleets is a key component for the success of such systems. However, efficiency of supply chains mostly depends on management decisions, which are often based on intuition and experience. Due to the increasing complexity of supply chain systems (which is the result of changes in customer preferences, the globalization of the economy and the stringy competition among companies), these decisions are often far from optimum. Another factor that causes difficulties in decision making is that different stages in supply chains are often supervised by different groups of people with different managing philosophies. From the early 1950s it became evident that a rigorous framework for analyzing the dynamics of supply chains and taking proper decisions could improve substantially the performance of the systems. Due to the resemblance of supply chains to engineering dynamical systems, control theory has provided a solid background for building such a framework. During the last half century many mathematical tools emerging from the control literature have been applied to the supply chain management problem. These tools vary from classical transfer function analysis to highly sophisticated control methodologies, such as model predictive control (MPC) and neuro-dynamic programming. The aim of this paper is to provide a review of this effort. The reader will find representative references of many alternative control philosophies and identify the advantages, weaknesses and complexities of each one. The bottom line of this review is that a joint co-operation between control experts and supply chain managers has the potential to introduce more realism to the dynamical models and develop improved supply chain management policies.

Equilibrium moisture content and heat of desorption of some vegetables

Abstract The equilibrium moisture content of potato, carrot, tomato, green pepper and onion was determined within the range of 10 to 90% water activity at three different temperatures (30, 45 and 60°C), using the standard static gravimetric method developed by the European Cooperation Project COST 90. The GAB equation was fitted to the experimental data, using the direct nonlinear regression analysis method and the agreement between experimental and calculated values was satisfactory. The net isosteric heat of desorption of water was determined from the equilibrium desorption data, using the Clausius-Clapeyron equation. An empirical exponential relationship between the net isosteric heat of sorption and the moisture content was proposed and validated.

A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem

Abstract The purpose of this paper is to present a new metaheuristic, termed the backtracking adaptive threshold accepting algorithm, for solving the heterogeneous fixed fleet vehicle routing problem (HFFVRP). The HFFVRP is a variant of the classical vehicle routing problem (VRP) and has attracted much less attention in the operational research (OR) literature than the classical VRP. It involves the design of a set of minimum cost routes, originating and terminating at a depot, for a fleet with fixed number of vehicles of each type, with various capacities, and variable costs to service a set of customers with known demands. The numerical results show that the proposed algorithm is robust and efficient. New best solutions are reported over a set of published benchmark problems.

BoneRoute: An Adaptive Memory-Based Method for Effective Fleet Management

This paper presents an adaptive memory-based method for solving the Capacitated Vehicle Routing Problem (CVRP), called BoneRoute. The CVRP deals with the problem of finding the optimal sequence of deliveries conducted by a fleet of homogeneous vehicles, based at one depot, to serve a set of customers. The computational performance of the BoneRoute was found to be very efficient, producing high quality solutions over two sets of well known case studies examined.

A fuzzy modeling application of CREAM methodology for human reliability analysis

Abstract This paper is using a fuzzy classification system for human reliability analysis in order to calculate the probability of erroneous actions according to CREAM in specific contexts e.g. maintenance tasks, in-field actions or control room operations in the running of a chemical plant. The complexities of such a system as well as the appropriate actions that have to be taken into consideration by the developers are analysed in detail. CREAM methodology has been selected among the most known and used methods for Human Reliability Analysis not only for being well-structured and precise, but also because it fits better in the general structure of the fuzzy logic. The first results from the application of the model are very promising and in accordance with CREAM. The numerical values produced by the model can be further used in the ‘classical’ risk assessment methods, such as event trees and fault trees, in order to calculate the overall occurrence frequency of a particular hazardous event. This is a pilot application that demonstrates the successful ‘translation’ of CREAM into a fuzzy logic model. However, the same model could be extended to cover also other industrial fields, like aviation technology and maritime transports.

Automatic identification of oil spills on satellite images

A fully automated system for the identification of possible oil spills present on Synthetic Aperture Radar (SAR) satellite images based on artificial intelligence fuzzy logic has been developed. Oil spills are recognized by experts as dark patterns of characteristic shape, in particular context. The system analyzes the satellite images and assigns the probability of a dark image shape to be an oil spill. The output consists of several images and tables providing the user with all relevant information for decision-making. The case study area was the Aegean Sea in Greece. The system responded very satisfactorily for all 35 images processed. The complete algorithmic procedure was coded in MS Visual C++ 6.0 in a stand-alone dynamic link library (dll) to be linked with any sort of application under any variant of MS Windows operating system.

A GIS-based decision support system for planning urban transportation policies

Abstract A decision support system (DSS) integrated in a geographical information system (GIS) for the analysis and evaluation of different transport policies is presented. The objective of the tool is to assist transport administrators enhance the efficiency of the transportation supply while improving environmental and energy indicators. The DDS works on three levels. The first performs the transport network analysis, the second assesses the energy consumption and pollutant emissions and the third evaluates the several policies selected. Road traffic is simulated using a deterministic, multi-modal traffic assignment model with capacity constraints. The model allows the estimation of traffic flow patterns within each link of the road network starting from the knowledge of the network characteristics and traffic demand. Energy consumption and pollutant emission calculations are based on the methodology developed by the CORINAIR working group. The evaluation of each policy scenario is based on a number of traffic, environmental and energy indicators. A multi-criteria analysis, where decision is based upon judging over appropriate weighted criteria, is adopted. Models are integrated in a GIS environment, which serves as the repository of the data as well as the user interface of the tool. The use of the tool is demonstrated through characteristic case studies on the Greater Athens Area in Greece. Two policy measures, one concerning the extension of the region where half of the private cars are prohibited from entering to the Municipality of Athens and the other the reduction of parking places in the same region by 50% are evaluated.

A meta-heuristic algorithm for the efficient distribution of perishable foods

Abstract A fast and robust algorithm for solving the fresh milk distribution problem for one of the biggest diary companies in Greece was developed. This particular problem was formulated as a Heterogeneous Fixed Fleet Vehicle Routing Problem (HFFVRP) for which, due to its high computational complexity, no exact algorithm ever has been used to solve it. In this study, a threshold-accepting based algorithm was developed aiming to satisfy the needs of the company that plans to use this methodology repeatedly to schedule their distribution many times a week. For this purpose, the proposed formulation was implemented in an efficient and reliable computer code. The algorithm manages to provide practical solutions and the early findings indicate considerable improvements in the operational performance of the company.

A Hybrid Metaheuristic Algorithm for the Integrated Vehicle Routing and Three-Dimensional Container-Loading Problem

This paper examines a recently addressed practical variant of the capacitated vehicle routing problem (VRP) called the capacitated vehicle routing problem with 3-D loading constraints (3L-CVRP). This problem considers customer demand to be formed by 3-D rectangular items. Additional loading constraints often encountered in real-life applications of transportation logistics are imposed on the examined problem model. In addition to 3L-CVRP, we also introduce and solve a new practical problem version that was dictated by a transportation logistics company and covers cases in which transported items are manually unloaded from the loading spaces of the vehicles. Both problem versions are solved by a hybrid metaheuristic methodology that combines the strategies of tabu search (TS) and guided local search (GLS). The loading characteristics are tackled by employing a collection of packing heuristics. The proposed algorithms robustness was tested for both problem versions, solving benchmark instances derived from the literature and new benchmark problems with diverse features in terms of customer set size and transported-item dimensions. It produced fine results, improving most of the best solutions that were previously reported.

DRYING KINETICS OF SOME FRUITS

ABSTRACT Drying kinetics of four Fruits (namely, apple, pear, kiwi and banana) were studied by introducing an one-parameter empirical mass transfer model, involving a characteristic parameter (drying constant), as a function of process variables. The model was tested with data produced in a laboratory dryer, using non-linear regression analysis. The investigation involved a wide range of characteristic dimensions of samples and air conditions (temperature, humidity, and superficial velocity). The parameters of the model considered were found to be greatly affected by sample characteristic dimension and air temperature. The model also involved the equilibrium material moisture content which was formulated in the form of the GAB equation. Its parameters were evaluated by means of non-linear regression analysis to independent experiments covering two process variables (temperature and water activity of the surrounding air).