Decision-makers always strive to build transport systems that are both profitable and sustainable. Such systems
seek to satisfy transportation requirements while minimizing adverse environmental effects and enhancing economic
viability. Cost savings and the reduction of the environmental impact can be boosted by improving the
supply chain management and freight transportation efficiency. In the transportation systems, energy conservation,
waste reduction, recyclable packaging, plastic reduction and sustainable transportation can majorly contribute to
the environmental sustainability. During transportation, several types of vehicles are used and generally these vehicles
use different type of fuels like petrol, diesel, CNG etc. These vehicles emit green house gases that pollute the
environment. In this study, an entropy based multi-objective 4D transportation problem with breakable and substitute
items is developed and examined in order to maximize profit and reduce the carbon emissions. The items have
been purchased at various depots at various prices. Different types of breakable/replacement items are delivered via
different routes using various types of vehicles having varying capacities. All the parameters have been taken to be
zigzag uncertain variables. Different models are developed in accordance with the management and the customer
decisions regarding the substitutability of items. Chance-constrained programming has been used to transform the
equivalent crisp models. All the models have been solved using the intuitionistic fuzzy programming technique
using the LINGO 19.0 optimization solver with x64-based system type and Intel(R) Pentium(R) CPU 4405U @
2.10GHz, 2100 Mhz, 2 Core(s) Processor. A real life based numerical problem is presented and solved to validate
the concept and the results are compared with respect to the nature of the obtained solution.