No abstract

One of the most important aspects affecting the performance of a supply chain is the management of inventories. Managing inventory in complex supply chains is typically difficult, and may have a significant impact on the customer service level and system-wide costs. The main challenge of inventory management is that almost every inventory problem involves multiple and conflicting objectives that need to be optimized simultaneously. In this paper, we present an efficient way using simulation-based optimization approach to determine the optimal inventory control parameters of a multi-echelon production-inventory system under a stochastic environment. The Pareto dominance concept is implemented to find a set of near optimal solutions for determining the best trade-off between objectives. The Multi-objective Particle Swarm Optimization (MOPSO) algorithm is used to determine the appropriate inventory control parameters to minimize the total inventory cost and maximize the service level. To evaluate the control parameters generated by the MOPSO, an object-oriented framework for developing the simulation model is presented. Finally, we provide a real-world case study of a major food product supply chain to demonstrate the use of proposed approach and enable decision making at inventory management. The proposed algorithm is compared with existing multi-objective genetic algorithm (NSGA-II).

Purpose The purpose of this paper is to design a model of the port performance metrics for improving the quality in ports by integration of six sigma and system dynamics (SD) approach. Design/methodology/approach The port performance is measured by the sigma value (SV), the process capability indices (PCIs), and the cost of poor quality (COPQ) as the performance metrics. A port is a complex system that requires SD as an appropriate tool to simulate the model dynamically. The performance metrics focus on measuring the port performance in the entire flow of material in the cargo handling process. Findings With this model, the changing of the SV, the PCIs, and the COPQ can be identified and analyzed the results to improve the performance in ports. These metrics are utilized to eliminate “waste” in the cargo handling process at ports. This waste consists of lost and damaged cargo, equipment and transporter breakdown, and equipment and transporter delay time. The port performance metrics model can assess the causal relationships in ports as a complex system. Originality/value Studies on integration between the six sigma model and SD in ports are few and relatively limited. The port’s performance can be measured directly using the SV, the PCIs, and the COPQ in the simulation. The port performance metrics model will give the decision makers to make some scenarios to contribute for the optimization of performance in ports.

Purpose – This purpose of this paper is to investigate the location problem of supermarkets, feeding by material the mixed model assembly lines using tow trains. It determines the number and the locations of these supermarkets to minimize transportation and inventory fixed costs of the system. Design/methodology/approach – This is done using integer programming model and real genetic algorithm (RGA) in which custom chromosomes representation, two custom mating and two custom mutation operators were proposed. Findings – The performance of RGA is very good since it gives results that are very close or identical to the optimal ones in reasonable CPU time. Research limitations/implications – The study is applicable only if a group of supermarkets feed the same assembly line. Originality/value – For the first time in supermarket location problem, limitation on availability of some areas for possible supermarkets ' locations and capacity of the supermarkets were taken into consideration.

Over the past few years, the biogas sector has experienced an important growth in the number of biogas installations all over Europe, and consequently, the quantity of digestate also has had a significant increase. In Europe, biogas production by anaerobic digestion (AD) is a common source of renewable energy and the current amount of installations is around 13,000. Together with biogas, digestate is one of the two main by products resulting from the biogas process. The digested effluent is a liquid product rich in nitrogen (N), phosphorus (P), potassium (K) and micronutrients. Therefore, there is a wide variety of digestate utilization depending on the quality, the origin of the feedstock, the operating conditions of the process as well as the phase of the by-product. The most common end uses are biofertilizer and soil amendment, due to its essential characteristics and when the quality is adequate for agriculture use. Before land application, environmental and agronomic reasons affect the storage of the digestate for a required period of time, in the biogas installations or near the area of application. Hence, the increasing production of digestate, the low solids content of whole digestate and the vulnerability of several land areas to the amount of nitrate and phosphate in Europe, convert the biofertilizer into a bottleneck for the biogas sector, due to the difficulty for its management.This paper contains an extensive review of the technical literature regarding digestate distribution. The objectives of this paper were to identify and analyse the current digestate distribution systems; storage and transport in Europe.