A bi-objective optimization model for a carbon cap jit distribution network

The environmental protection concerns and legislation are pushing companies to redesign and plan their activities in an environmental friendly manner. This will probably be done by constraining companies to emit less than a given amount of carbon dioxide per product that is being produced and transported. In addition, some companies may volunteer to reduce their carbon footprint. Consequently, companies will face new constraints that force them to reduce carbon emissions while still minimizing production and transportation costs. Transportation is at the heart of logistics activities and is one of the leading sources of greenhouse gas emissions. The emitted carbon dioxide through transportation activities is accounting for almost 80% of the total greenhouse gas emissions. The need to implement Just-In-Time (JIT) strategy for transporting small batch sizes seems to beagainst environmental concerns. The JIT principles favor small and frequent deliveries by many small rush transports with multiple regional warehouses. Although several attempts have been made to analyze green supply chain networks, little attention has been paid to develop JIT distribution models in carbon constrained environment. Incorporation of environmental objectives and constraints with JIT distribution will generate new problems resulting in new combinatorial optimization models. In addition, these objectives and constraints will add to the model complexities. Both areas require to be investigated. In this research, a bi-objective carbon-capped logistic model was developed for a JIT distribution that takes into account different carbon emission constraints. The objectives include minimization of total costs and carbon cap. Since the studied problem is Non-deterministic Polynomial-time Hard (NP-Hard), a nondominated sorting genetic algorithm-II (NSGA-II) was employed to solve the problem. For validation and verification of the obtained results, non-dominated ranking genetic algorithm (NRGA) was applied. Then, Taguchi approach was employed to tune the parameters of both algorithms; their performances were then compared in terms of some multi-objective performance measures. For further improvements of NSGA-II, a modified firefly algorithm as local searcher was applied. Seven problems with different sizes of small, medium, and large were designed in order to simulate the different cases. The findings have significant implications for the understanding of how varying carbon cap could significantly affect total logistics costs and total carbon emission. More specifically, the results also demonstrated devising policies that enable companies to decide when and how to fulfill the required carbon cap could let firms fulfill these caps at significantly lower costs with lower carbon emission. In addition to these findings, the performance of the proposed solution methodology demonstrated higher efficiency particularly in terms of less CPU time usage by 6.62% and higher quality of obtained solutions by 5.14% on average for different sizes of the problem as compared to the classical NSGA-II

Learning competency, entrepreneurial orientation entrepreneurial innovativeness, and business growth: A Study among Malaysian Chinese entrepreneurs

It has been widely acknowledged that Malaysian Chinese entrepreneurs significantly contribute in the success of SMEs’ businesses. This study examined the effect of entrepreneurial innovativeness on the wholesale and retail SMEs’ business growth under the moderating impacts of market turbulence among Chinese entrepreneurs. Additionally, learning competency and entrepreneurial orientation were also assessed entrepreneurial innovativeness’ antecedents. In addition, Composition Based View (CBV) as well as Strategic Contingency Theory (SCT) were identified as the underpinning theories for this study. Six hypotheses were developed according to the proposed research model and the data were gathered from target respondents using convenience. A total of 110 retail SMEs’ owners from Kuala Lumpur as well as Selangor participated in a face-to-face survey procedure. The data were collected at one point of time across the sample population. The findings revealed the positive and significant impacts of learning competency as well as entrepreneurial orientation on the innovativeness. Likewise, based on the findings, market turbulence as a moderator also influenced significantly on business growth. Furthermore, entrepreneurial innovativeness was found as a mediator between learning competency and business growth as well as between entrepreneurial orientation and business growth

An integrated production-distribution planning in green supply chain: a multi-objective evolutionary approach

The goal of this research is to develop a novel multi-objective mathematical model in a green supply chain network consisting of manufacturers, distribution centers and dealers in an automotive manufacture case study. The main objectives considered are: minimizing the costs of production, distribution, holding and shortage cost at dealers as well as minimizing environmental impact of logistic network. In addition to minimizing the costs and environmental impacts particularly the emission of CO2, the model can determine the green economic production quantity using Just-In-Time logistics. Furthermore, multi-objective genetic algorithm is applied in order to minimize these two conflicting objectives simultaneously. Finally, the performance of the proposed model is evaluated by comparing the obtained Pareto fronts from Moga and goal attainment programing solver in Matlab

Comparison of two simulation software for modeling a construction process

Construction process complexities lead to many difficulties imposed on construction planners and designers who are facing with different issues such as developing new methods or solving problems during a construction process. In order to solve these problems in construction industry, simulation can be an acceptable solution. In this regard, graphical methods have become a useful tool for process simulation. To do construction process simulation with a suitable graphical display, many simulation software are developed such as PROMODEL, SDESA, and etc. This paper aims at comparing two simulation tools (software), ARENA 13 and WITNESS 2004 Manufacturing Edition, for making a construction process simulation model. It shows that both software produce almost the same results and outputs for a given construction process. Also, the paper shows different kinds of features and reports provided by ARENA 13 and WITNESS 2004 Manufacturing Edition

An optimization study of a palm oil-based regional bio-energy supply chain under carbon pricing and trading policies

Biomass residues due to their low bulk density typically require frequent transportation from biomass plantations in rural areas to conversion bio-energy power plants. This issue contrasts with environmental protection strategies, especially when power plants are facing different carbon reduction policies that enforce them to emit less than a given specific carbon amount. Although several researchers have investigated bio-energy supply chains concerning environmental policies, the majority of studies have been devoted to strategic decisions over a single planning period. This paper presents a multi-period bio-energy supply chain under carbon pricing (carbon tax) and carbon trading (cap-and-trade) policies at the tactical planning level. A mixed-integer linear programming model was adopted to optimize the proposed regional oil-palm biomass-to-bio-energy supply chain planning model. The numerical results indicate that when carbon pricing is in place when carbon tax increases linearly, carbon emissions’ reductions have a nonlinear trend, whereas both cost increase and carbon emissions’ reductions have a relatively upward trend in the carbon trading scheme. This paper also presents the sensitivity analysis of the proposed model regarding cost, emissions’ generation and supply chain performance. Finally, the paper recommends several significant practical implications and policy-making insights for managers and policymakers

A huiristic method for information scaling in manufacturing organizations

Protecting information assets is very vital to the core survival of an organization. By increasing in cyber-attacks and viruses worldwide, it has become essential for organizations to adopt innovative and rigorous procedures to keep these vital assets out of the reach of exploiters. Although worldwide complying with an international information security standard such as ISO 27001 has been raised, with over 7000 registered certificates, few Iranian companies are under ISO 27001 certified. Also organization needs to perform a risk assessment in order to determine the organization's asset exposure to risk and determine the best way to manage this. The determination of risk within the methodology is based upon the standard formula, which the risk is calculated from the multiplication of the asset value, threats and vulnerability. The ISO 27001 requires is that 'An appropriate risk assessment shall be undertaken'. One of the main factors for risk assessment is identifying and scoring of Information asset in this process. Due to different values of asset in organizations, the main purpose of this study is to identify and investigate a weighted method to assign different values of assets in order to minimize vulnerability in manufacturing systems. This study also aims at improving asset value scoring by using heuristic methods. A real world case study was selected for implementation of this approach based on ISO27001 in Ira