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

Supplier selection: a fuzzy-ANP approach

The main goal of this paper is to develop a framework to support the supplier selection process in an Iranian automotive industry. Although numerous criteria are being used for the selection of suitable supplier, selection of the critical factors in conformance to the specification of the automotive industries is less investigated. In order to fill this gap, this research was carried out to systematically propose a framework comprising of the most critical factors for the aim of supplier selection. A literature survey was conducted and measures for assessing the suppliers were extracted. Nominated Group Technique (NGT) was deployed to extract the most critical performance measures from the initial list. Seven measures were found to be proper for the supplier selection process. A Fuzzy Analytical Network Process (FANP) was then proposed to weight the extracted measures and determine their importance level. The model was then implemented to assist an automotive company for the aim of its supplier selection