Optimized container management system

A computer-implemented method of optimized container management system, the method comprising:

• receiving, as input from a transport management enterprise application, a plurality of booking requests and customer information, safety stock and maximum stock configuration information, and cost information associated with the plurality of booking requests at a solver in a container management system, wherein the plurality of booking requests include customer locations, booking time, container type, movement mode, and wherein the plurality of booking requests are automatically provided by the transport management enterprise application to trigger execution of a solver algorithm at the solver;
• executing the solver algorithm implemented at the solver in the container management system, wherein the solver algorithm includes a pick-up solver, a return solver, and a street-turn solver, wherein the solver algorithm generates a bipartite graph including a plurality of nodes representing the customer locations and the depot locations for fulfilling the plurality of booking requests, and wherein based on a movement mode of a received booking request, at least one of the pick-up solver, the return solver, and the street-turn solver is automatically invoked;
• in response to determining that the movement mode indicated at a first booking request is for a container pick-up,
• generating, by the pick-up solver at a first stage based on a pick-up container balancing criteria defined based on the received safety stock and maximum stock configuration information, an edge at the bipartite graph between a first customer location from the customer locations and a first depot location from the depot locations when the pick-up container balancing criteria is satisfied for the first depot location, wherein the first customer location is associated with the first booking request, and
• based on identifying a booking request that is not fulfilled with the pick-up container balancing criteria, generating, by the pick-up solver at a second stage based on a cost minimization criteria received as input at the solver, an edge between a customer location from the customer locations and a depot location from the depot locations based on the cost minimization criteria;
• based on the bipartite graph and evaluation of edges between the customer locations and correspondingly associated depot locations based on the pick-up container balancing criteria and the cost minimization criteria, automatically generating a table including records associated with the customer locations defined with the plurality of booking requests and the correspondingly associated depot locations, wherein the table includes corresponding relations between the first customer location and a set of depot locations, and wherein a first record in the table defines a relation between the first customer location and the first depot location, a result value, a cost value, and an assigning identification information identifying that the first customer location is assigned to the first depot location, as an optimal pick-up depot location for the first customer location;
• based on an evaluation of the table and the assigning identification information, determining, by the solver, optimal schedules and routes for the plurality of booking requests according to the pick-up container balancing criteria and if not satisfied based on the cost minimization criteria to fulfill the plurality of booking requests as input at the solver;
• executing a return solver algorithm implemented at the return solver in the container management system when the movement mode is container return;
• generating a set of edges, based on the executed return solver algorithm at the return solver, between the customer locations and the depot locations at the bipartite graph based on a return container balancing criteria;
• based on the bipartite graph with the set of edges satisfying the return container balancing criteria, identifying and assigning a return depot location corresponding to the first customer location from the customer locations to fulfill a received booking request from the plurality of booking requests, the booking request is for return of containers at the first customer location of the customer locations;
• in response to the received booking request, generating, by the return solver, a return route corresponding to the booking request for the first customer location, wherein the return route identifies the return depot location corresponding to the first customer location for transporting the return containers;
• based on executing a street-turn solver algorithm at the street-turn solver, generating a path for repositioning of containers between two customer locations from the customer locations by generating an edge between the two customer locations based on a movement mode being street-turn, a specified booking time interval, the container type and an operation cost;
• and
• generating and transmitting instructions from the street-turn solver for executing the repositioning of the containers based on the generated path.

A computer system for optimized container management, comprising:

• a computer memory to store program code;
• and
• a processor to execute the program code to:
• receive, as input from a transport management enterprise application, a plurality of booking requests and customer information, safety stock and maximum stock configuration information, and cost information associated with the plurality of booking requests at a solver in a container management system, wherein the plurality of booking requests include customer locations, booking time, container type, movement mode, and wherein the plurality of booking requests are automatically provided by the transport management enterprise application to trigger execution of a solver algorithm at the solver;
• execute the solver algorithm implemented at the solver in the container management system, wherein the solver algorithm includes a pick-up solver, a return solver, and a street-turn solver, wherein the solver algorithm generates a bipartite graph including a plurality of nodes representing the customer locations and the depot locations for fulfilling the plurality of booking requests, and wherein based on a movement mode of a received booking request, at least one of the pick-up solver, the return solver, and the street-turn solver is automatically invoked;
• in response to determining that the movement mode indicated at a first booking request is for a container pick-up,
• generate, by the pick-up solver at a first stage based on a pick-up container balancing criteria defined based on the received safety stock and maximum stock configuration information, an edge at the bipartite graph between a first customer location from the customer locations and a first depot location from the depot locations when the pick-up container balancing criteria is satisfied for the first depot location, wherein the first customer location is associated with the first booking request, and
• based on identifying a booking request that is not fulfilled with the pick-up container balancing criteria, generate, by the pick-up solver at a second stage based on a cost minimization criteria received as input at the solver, an edge between a customer location from the customer locations and a depot location from the depot locations based on the cost minimization criteria;
• based on the bipartite graph and evaluation of edges between the customer locations and correspondingly associated depot locations based on the pick-up container balancing criteria and the cost minimization criteria, automatically generate a table including records associated with the customer locations defined with the plurality of booking requests and the correspondingly associated depot locations, wherein the table includes corresponding relations between the first customer location and a set of depot locations, and wherein a first record in the table defines a relation between the first customer location and the first depot location, a result value, a cost value, and an assigning identification information identifying that the first customer location is assigned to the first depot location, as an optimal pick-up depot location for the first customer location;
• based on an evaluation of the table and the assigning identification information, determine, by the solver, optimal schedules and routes for the plurality of booking requests according to the pick-up container balancing criteria and if not satisfied based on the cost minimization criteria to fulfill the plurality of booking requests as input at the solver;
• execute a return solver algorithm implemented at the return solver in the container management system when the movement mode is container return;
• generate a set edges, based on the executed return solver algorithm at the return solver, between the customer locations and the depot locations at the bipartite graph based on a return container balancing criteria;
• based on the bipartite graph with the set of edges satisfying the return container balancing criteria, identify and assign a return depot location corresponding to the first customer location from the customer locations to fulfill a received booking request from the plurality of booking requests, the booking request is for return of containers at the first customer location of the customer locations;
• in response to the received booking request, generate, by the return solver, a return route corresponding to the booking request for the first customer location, wherein the return route identifies the return depot location corresponding to the first customer location for transporting the return containers;
• based on executing a street-turn solver algorithm at the street-turn solver, generate a path for repositioning of containers between two customer locations from the customer locations by generating an edge between the two customer locations based on a movement mode being street-turn, a specified booking time interval, the container type and an operation cost;
• and
• generate and transmit instructions from the street-turn solver for executing the repositioning of the containers based on the generated path.