The separation at the source of Municipal Solid Waste (MSW) is an initiative that facilitates the subsequent recycling work and contributes to palliate the negative impacts of the traditional unsorted collection system. This paper presents a multi-objective integer linear programming model of the determination of the optimal location of assorted waste bins in an urban area. We consider, jointly, the objectives of minimizing the investment cost and the average distance from the dwellings to the bins. The model was applied in simulated instances of an Argentinian medium-size city, contributing to the transition from the current door-to-door based system to a community bins system. To solve this problem, we apply both the weighting method, which has been used to solve similar problems in the literature, and a novel version of the augmented ε-constraint method (AUGMECON2). The results over simulated scenarios show that, in general, AUGMECON2 has a better performance, yielding a larger number of efficient solutions at lower computation times.

Today, urban areas have been considerably expanded, which has caused numerous problems due to the large population in metropolitan areas. City logistics models can be effective in solving complicated problems such as traffic congestion, air pollution, accidents, and high energy consumption rate. The present paper proposes a bi-objective mathematical model for designing a city logistics distribution network in order to minimize the economic and environmental costs as well as the response time. The proposed model would make decisions on the location and allocation problems in the city logistics distribution network. In fact, the objective of the problem is to select some fixed sites in order to construct the city distribution centers. The demand for commodities is considered probabilistic and the network is modeled based on the queuing theory. Furthermore, in the proposed model, the policy of putting tax on carbon and applying the low-carbon emission resources are used for establishment at the city distribution centers. Afterwards, in order to validate the proposed model, a numerical example is generated and, then, the results obtained from solving the model via epsilon constraint method are presented. Analysis of the results in the present study indicates that the proposed model was highly efficient in achieving its objectives. Finally, there are some suggestions for future studies that can be taken into account.

Increasing in attentions to the environment, city legislative and social problems make companies change their prospects towards supply chain management and design sustainable transportation networks. In this paper, two-stage problem have been investigated in which the transportation stage is considered before Location-Routing Problem, so we call it Transportation-Location-Routing Problem (TLRP). It is an extension of the two-echelon Location-Routing Problem. In the first stage, there is a transportation problem with truck capacity limitation. Furthermore, customers’ time windows should be met in the second stage to make the mode more realistic. Minimization of distribution cost, fuel consumption, and carbon dioxide emission along with balancing the workloads for city drivers are considered as the objective functions of the mathematical model to design a sustainable distribution network. To tackle these conflicting objectives, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) are applied to solve the problem. A new customized chromosome based on a priority based technique is presented for the problem. Due to the three comparison metrics for multi-objective problems, with tolerating a little more computational time, MOPSO has the better performance in this problem than NSGA-II.

There is an increase in awareness about sustainable manufacturing process. Manufacturing industries are backbone of a country’s economy. Although it is important but there is a great concern about consumption of resources and waste creation. The primary aim of this study was to explore sustainability concern in turning process in an Indian machining industry. The effect of cutting parameters, Speed/Feed/Depth of Cut, the machining environment, Dry/MQL/Wet, and the type of cutting tool on sustainability factors under study were observed. Analysis of Variance (ANOVA) was used to analyse the data obtained from experimentation in a small scale machining industry. The process is modelled mathematically using response surface methodology (RSM).The economic and environmental aspect like surface roughness, material removal rate and energy consumption were considered as sustainability factors. The model helps to understand the effect of the cutting parameters and conditions on surface finish, energy consumption, and material removal rate. The process was optimized for minimum power consumption considering environmental concern as prime importance. Studies suggest that the cutting environment and tool type influenced on the power consumption during turning process. Extended form of the proposed model could be useful to predict the environmental impact due to machining process, which would bring environmental concern into conventional machining.

Sustainability in project operations such as financial, social and environmental sustainability is one of the most prominent issues of the present times to address. The increased focus on sus-tainable business operations has changed the viewpoint of researchers and corporate community towards the project management. Today sustainability in business operations along with sustain-ability of natural and environmental resources are of paramount significance which has further caused a huge impact on conception, planning, scheduling and execution of the project manage-ment activities. In this paper, a literature review between 1987 and 2018 on different issues af-fecting the sustainability in project management is carried out. The present study also identifies and discusses the future possibilities to apply computational procedures in order to estimate and optimize the sustainability issues in the management of projects, for example the computational evolutionary algorithms can be applied to formulate the multi-objective decision-making problem after considering critical factors of sustainability in the projects and then yielding optimized solu-tions for the formulated problem to achieve sustainability in the projects. A new integrated framework with the inclusion of feedback function for assessment of each decision and actions taken towards the sustainability of the projects is also identified and presented.

Cement is the single most important and profitable product in the building material sector. With the economic boom, in India, Indian cement industry is a market of opportunities waiting to be tapped. However, at the same time cement industry is also experiencing a surge in demand. Production of Cement will always release carbon dioxide and change in the climate of the earth that is why despite its profitability, the cement industry faces many challenges regarding environmental concerns and sustainability issues. In order to minimize the impact of all of the above mentioned issues, it is clear that the cement and construction industry will have to adapt to remain sustainable and in this process a number of innovative and new practices have to be adopted. The objective of this paper is to analyze the gap between the existing reporting practices and level of disclosure desired by stakeholders of cement companies and to identify the areas under which Indian Cement companies can report accounting information in sustainable way. Furthermore it is also required to align the reporting is as per stakeholder’s requirement. The accounting areas of reporting will be explored so that the requirements of reporting in terms of financial character can be filled in. This may lead to change in the practices under which the current financial statement provides financial information of sustainable activity as non-financial activity and its cost has been shown in the miscellaneous expenditure.