ABSTRACT This study proposes automating an air conditioning system for drying and storing agricultural products. The main objective is to precisely control key parameters of the air, namely temperature, relative humidity, and air velocity, to optimize the drying process. The framework required for constructing and operating the automated air conditioner is explained in detail. Specifically, we describe the conditioning unit, the automation hardware, the control strategies employed to regulate temperature, relative humidity, and air velocity, and discuss the safety measures and human-machine interfaces of the system. Experimental validation of the proposed system is presented, along with results and discussions demonstrating its successful control of drying air parameters across a wide range of desired conditions. products temperature humidity velocity process detail Specifically unit hardware humanmachine human machine presented conditions

Abstract Paper aims This study presents several business analytics tools that allow improving the tactical planning of the collection process for a Colombian solid-waste management company. Originality The extant literature of operations research/analytics applied to these systems focuses on facility location or vehicle routing. Tactical decisions are seldom studied in the operations research/analytics literature devoted to waste management systems. By contrast, the focus of this paper is on tactical decisions: fleet sizing, frequency assignment, route scheduling and internal resource allocation in a new waste transfer station. Research method We follow a multimethodology approach that uses mathematical programming, metaheuristics, and discrete event simulation. The models use historical information of the system, and the solution of a model are used as input data for the other models. Main findings Introducing a new waste transfer station allows an important reduction of the compactors fleet. However, to prevent a collapse in its internal operation an even operation is needed. This is achieved by rescheduling the routes to balance their arrival during the day. Additional benefits can be attained if some soft constraints are relaxed. Implications for theory and practice Practitioners looking for tactical planning tools on waste collection systems have here an example of their application and benefits. Improvements can be achieved by tactical planning without heavily disrupting decisions at the operational level.

Abstract Paper aims This paper studies a new optimization problem called the Electric Boat Charging Problem (EBCP), which is based on the application of electric mobility in a river transport operation problem. Originality This work pioneers the studies of the electric mobility on the river operations, by proposing the EBCP. This problem includes real features of the electric mobility such as nonlinear charging functions, battery degradation costs, and speed variation. Research method For solving the EBCP, we propose a Mixed-Integer Linear Programming (MILP) formulation. For testing our MILP formulation, we use a set of instances based on a future transport operation. We also analyze the impact of some problem parameters on the objective function, and decision variables. Main findings Our MILP formulation is capable to optimally solve different type of instances in competitive CPU times. The battery capacity and a time limit constraint have and important impact on the objective function and the decision-making variables. Implications for theory and practice We model the EBCP as a MILP formulation. This model allows to optimally solve industrial scale instances. Moreover, using a sensitivity analysis, we unveil that both the battery capacity and the time limit constraint of the EB route are critical parameters.