Trends in Emission Inventory of Marine Traffic for Port of Haifa

Located in the Middle East, Haifa Port serves both local and international trade interests (from Asia, Europe, America, Africa, etc.). Due to its strategic location, the port is part of the Belt and Road initiative. This research investigates Haifa Port’s emissions contribution to the existing daily emission inventory level in the area. This research is based on a developed full bottom-up model framework that looks at the single vessel daily voyage through its port call stages. The main data sources for vessel movements used in this research are the Israel Navy’s movements log and the Israel Administration of Shipping and Ports’ (ASP) operational vessel movements and cargo log. The Fuel Consumption (FC) data and Sulfur Content (SC) levels are based on official Israel ASP survey data. The observation years in this research are 2010–2018, with a focus on the Ocean-Going Vessel (OGV) type only. The results show that the vessel fleet calling at Israel ports mainly comprises vessels that have a lower engine tier grade (i.e., Tier 0 and 1), which is considered a heavy contributor to nitrogen oxide (NOx) pollution. The study recommends an additional cost charged (selective tariff) to reflect the external social cost linked to the single vessel air pollution combined with supportive technological infrastructure and economic incentive tools (e.g., electric subsidy) to attract or influence vessel owners to assign vessels equipped with new engine tier grades for calls at Israeli ports.

Designing a Medical Supply Chain Network Considering the Risk of Supply and Flexible Production in Two-Stage Uncertain Conditions

In the green supply chain approach, all the links that are put together to provide a product or service are considered, and strategic and operational decisions are made to increase the efficiency and effectiveness of the entire chain. At the same time, the environmental effects should be minimized. In this research, a nonlinear mixed-integer multiobjective model is developed to design a green closed-loop supply chain for medical products. In this supply chain, the echelons include supplier, manufacturer, warehouse, and customer in the forward supply chain and collection centers, repair services, and disposal centers in the reverse supply chain. In the proposed model, four objectives of customer satisfaction, environmental effects, supply risk, and total costs of the supply chain were considered. The developed model is implemented in a supply chain of medical products, and after optimizing the model, the main results including location and capacity of facilities, planning for flexible production, purchase of materials, service and maintenance plan, product transfer, and inventory level are determined and analyzed.

Production batch sizing and inventory level control using simulation software

Computer simulation has great application potential in the area of Production Engineering as a tool to support decision making as it allows to simulate the functioning of a real system through logical relationships, in order to observe its behavior under different scenarios. Which could not be practiced in the real system. In line with this aspect, the present work aims to present a report on the application of simulation for the design of production batches and inventory control, highlighting the process necessary for the construction of the generated simulation model, as well as the challenges and opportunities observed. In order to achieve the proposed objective, a literature review was carried out on the topics of interest; the choice and understanding of simulation software and; the survey of data from a large auto parts manufacturer located in the interior of the state of São Paulo. The main results were an increase in production volume from the inclusion and dimensioning of a buffer after the assembly process and a balance between the number of items of each component of the product structure in the supply with the real capacity of manufacturing cell processing. Cabe ressaltar que o modelo de simulação produto da pesquisa deste artigo pode ser aplicado como um sistema de apoio à decisão do gestor para a elaboração do planejamento estratégico e do planejamento operacional com o propósito de melhorar a capacidade de análise e decisão. It is important mentioning that the simulation model in this article can be applied as a support system decision for the preparation of strategic planning and operational planning, with the purpose of improving the analysis capacity for decision-making.

Cross-Border Internet of Things E-Commerce Warehouse Control System Based on TRIZ Theory

Cross-border e-commerce of the Internet of Things is affected by international situations and political factors. Supply chain interruption and returns will cause violent fluctuations in commodity inventory, making the inventory control of cross-border e-commerce very difficult. The TRIZ principle is utilized to solve the problem of the difficulty to evaluate the suppliers comprehensively in e-commerce warehouse management. The Markov algorithm is used to describe the change of inventory level. The cyclic expected time and cost function are constructed by the horizontal crossing method, updating the process and Martingale theory. The effect of the correlation between the demand and supply interruption on the optimal inventory control strategy is studied by simulation. The change of the optimal control strategy under the different interrupt and return types is analyzed, and the validity of the management system is verified.

The Effect of Working Capital Management on Profitability: Evidence from Malaysian Construction Firms

Working capital management is an essential part of a sound business. The main objective of this research is to investigate the effect of working capital management on profitability. The regression analysis was carried out on a panel sample of 30 construction firms listed on Bursa Malaysia over a five-year period from 2015 to 2019. The findings suggest that there is a significant positive relationship between Days Inventory Outstanding (DIO) and Gross Operating Profit (GOP) as well as a significant negative relationship between Days Payables Outstanding (DPO) and GOP. Thus, firms can maximise their profitability by maintaining higher inventory level and paying off creditors in a shorter time frame.

Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information

We consider the periodic review dynamic pricing and inventory control problem with fixed ordering cost. Demand is random and price dependent, and unsatisfied demand is backlogged. With complete demand information, the celebrated [Formula: see text] policy is proved to be optimal, where s and S are the reorder point and order-up-to level for ordering strategy, and [Formula: see text], a function of on-hand inventory level, characterizes the pricing strategy. In this paper, we consider incomplete demand information and develop online learning algorithms whose average profit approaches that of the optimal [Formula: see text] with a tight [Formula: see text] regret rate. A number of salient features differentiate our work from the existing online learning researches in the operations management (OM) literature. First, computing the optimal [Formula: see text] policy requires solving a dynamic programming (DP) over multiple periods involving unknown quantities, which is different from the majority of learning problems in OM that only require solving single-period optimization questions. It is hence challenging to establish stability results through DP recursions, which we accomplish by proving uniform convergence of the profit-to-go function. The necessity of analyzing action-dependent state transition over multiple periods resembles the reinforcement learning question, considerably more difficult than existing bandit learning algorithms. Second, the pricing function [Formula: see text] is of infinite dimension, and approaching it is much more challenging than approaching a finite number of parameters as seen in existing researches. The demand-price relationship is estimated based on upper confidence bound, but the confidence interval cannot be explicitly calculated due to the complexity of the DP recursion. Finally, because of the multiperiod nature of [Formula: see text] policies the actual distribution of the randomness in demand plays an important role in determining the optimal pricing strategy [Formula: see text], which is unknown to the learner a priori. In this paper, the demand randomness is approximated by an empirical distribution constructed using dependent samples, and a novel Wasserstein metric-based argument is employed to prove convergence of the empirical distribution. This paper was accepted by J. George Shanthikumar, big data analytics.

Two Level Trade Credit Policy Approach in Inventory Model with Expiration Rate and Stock Dependent Demand under Nonzero Inventory and Partial Backlogged Shortages

In present real life situations, the stock and expiration date directly impact on the demand of an item. In this context, this research work develops an inventory model for stock and expiration rate-dependent demand under a two-level trade credit policy. Specifically, the following three situations are studied: (i) trade credit policy without zero ending inventory; (ii) trade credit policy with zero ending inventory; (iii) trade credit policy with partial backlogged shortages. The proposed inventory model is formulated as a non-linear constrained optimization problem. Some theoretical results are derived, and an algorithm is stated in order to solve the proposed inventory model. The main objective of the inventory model is to determine the optimal cycle length, the optimal ending inventory level, and the optimal number of units displayed which maximize the total profit. Some numerical examples are solved. Finally, a sensitivity analysis is done with the aim to see the impacts of a variation of the input parameters on the decision variables and the total profit.

IMPLEMENTASI CONSIGNMENT STOCK DAN MARKETING MIX STRATEGY 4P UNTUK MENURUNKAN PERSEDIAAN PADA PART AND SERVICE DEPARTMENT DI PT. COAL MINING

The company has complaints about the high inventory which is a burden to the company. Based on the observations, the inventory level in the Part and Service department in July with a value of days on inventory of 149 days exceeded the maximum target of 120 days. This study aims to find a way to reduce the value of days on inventory and deadstock as much as possible so that it can reduce costs. To find a solution to the problem, an ABC, SWOT, and business solution analysis was carried out through focus group discussions (FGD) with seniors and experts on this issue. From all the results of the analysis it was agreed that the consignment stock method and the 4P mix strategy could be implemented. After implementing this idea, good results were obtained, namely a decrease in inventory of Rp. 37,347,572,356 to Rp. 27,650,733,680 (down 26%) and the value of days on inventory from 149 days to 98 days and also a decrease in deadstock from Rp. 11,641,000,000 to Rp. 8,626,000,000 (down 26%)AbstrakPerusahaan memiliki keluhan akan tingginya inventory (inventory) yang menjadi beban bagi perusahaan. Berdasarkan hasil observasi, tingkat inventory pada DePartemen Part and Service pada bulan Juli 2018 ditemukan nilai days on inventory sebesar 149 hari yang mana telah melebihi batas maksimum yaitu 120 hari. Penelitian ini bertujuan untuk menemukan cara agar nilai days on inventory dan deadstock dapat ditekan semaksimal mungkin sehingga dapat menekan cost. Untuk mencari solusi permasalahan dilakukan analisis ABC, SWOT, dan solusi bisnis melalui focus group discussion (FGD) dengan para senior dan ahli dalam masalah ini. Dari seluruh hasil analisis disepakati bahwa metode consignment stock dan mix strategy 4P lah yang dapat diimplementasikan. Setelah implementasi ide tersebut, didapatkan hasil yang baik yakni penurunan inventory Rp 37.347.572.356 menjadi Rp 27.650.733.680 (turun 26%) serta nilai days on inventory dari 149 hari menjadi 98 hari dan juga penurunan atas deadstock dari Rp 11.641.000.000 menjadi Rp 8.626.000.000 (turun 26%).

Steady State Analysis of Impulse Customers and Cancellation Policy in Queueing-Inventory System

This article discusses the queueing-inventory model with a cancellation policy and two classes of customers. The two classes of customers are named ordinary and impulse customers. A customer who does not plan to buy the product when entering the system is called an impulse customer. Suppose the customer enters into the system to buy the product with a plan is called ordinary customer. The system consists of a pool of finite waiting areas of size N and maximum S items in the inventory. The ordinary customer can move to the pooled place if they find that the inventory is empty under the Bernoulli schedule. In such a situation, impulse customers are not allowed to enter into the pooled place. Additionally, the pooled customers buy the product whenever they find positive inventory. If the inventory level falls to s, the replenishment of Q items is to be replaced immediately under the (s, Q) ordering principle. Both arrival streams occur according to the independent Markovian arrival process (MAP), and lead time follows an exponential distribution. In addition, the system allows the cancellation of the purchased item only when there exist fewer than S items in the inventory. Here, the time between two successive cancellations of the purchased item is assumed to be exponentially distributed. The Gaver algorithm is used to obtain the stationary probability vector of the system in the steady-state. Further, the necessary numerical interpretations are investigated to enhance the proposed model.

Information technology for the analysis of the dynamic of the carbon balance of forests in Poland

Forest management involves the use of large areas of land and a large amount of related information. Therefore, the use of geographic information technologies (GIS) is substantiated for the processing, analysis, and visualization of information in forest ecosystems. Green plants and trees deposit carbon and retain it for a long time, they are the main absorbers of carbon on land, so to determine the carbon balance the study of wood growth, accumulation of phytomass in forest ecosystems is necessary. The purpose of the work is to develop a toolkit for determining the geo-distributed phytomass of forests for the calculation of deposited carbon according to statistical data of planting stock, species composition, age class, and other silvicultural and taxonomic indicators provided by the official sources. The article provides a description of Polish forests, GIS analysis of tabular data on taxonomic indicators of forest ecosystems, diagrams, and digital maps of forests. The analysis of the forests state in some voivodships of Poland in 2009 and 2019 was conducted to assess emissions and removals of greenhouse gases by forest ecosystems. The three-level scheme of greenhouse gas inventory recommended by the IPCC technique is described. To carry out the inventory, a multilevel mathematical model is used, which includes: the highest level of inventory (level of national inventory), the middle level of inventory (level of region or district), and the inventory lowest level (level of the elementary plots). A comparative analysis of forestry and tax indicators of Polish forests for the period from 2009 to 2019 and the methods used to calculate greenhouse gas emissions and removals are presented. The amount of carbon deposited over a ten-year period by Polish forest ecosystems has been determined. The architecture of geographic information technology for spatial analysis of carbon deposition and greenhouse gas emissions in the Polish forestry sector has been improved and supplemented. Calculations of the deposited carbon were made according to statistical data of planting stock, species composition, age class, and other silvicultural and taxonomic indicators, which are taken from the official sources. The geoinformation approach to the comparative analysis of greenhouse gases for different time intervals is based on the use of the appropriate digital map layers, mathematical models of inventory, statistical information on business results, as well as the use of a number of other specific parameters describing complex greenhouse gas emission and absorption processes. Keywords: GIS; digital maps; greenhouse gases; forests of Poland.