Choosing proper locations of urban transit hubs has always been one of the critical concerns facing urban transportation planning agencies in China. This study proposes a mixed integer optimal location model for urban transit hubs, with the objective to minimize the demand-weighted total travel time, when explicitly taking into account Traffic Analysis Zones (TAZs) as demand origins or destinat...

This paper considers a dairy industry problem on integrated planning and scheduling of set yoghurt production. A mixed integer linear programming formulation is introduced to integrate tactical and operational decisions and a heuristic approach is proposed to decompose time buckets of the decisions. The decomposition heuristic improves computational efficiency by solving big bucket planning and...

vehicle routing problem (vrp) is one of the major problems in the transportation and distribution planning. in the most previous studies, the objective of vrp models was distance and vehicle related costs. however in many industrial cases along with routing distance, vehicle loading amount is a factor of cost function. in this paper, we formulate a mixed integer non-linear programming (minlp) m...

this paper studies the multi-stage supply chain system (msscm) controlled by the kanban mechanism. in the kanban system, decision making is based on the number of kanbans as well as batch sizes. a kanban mechanism is employed to assist in linking different production processes in a supply chain system in order to implement the scope of just-in-time (jit) philosophy. for a msscm, a mixed-integer...

this paper addresses the mixed integer reliability redundancy allocation problems to determine simultaneous allocation of optimal reliability and redundancy level of components based on three objective goals. system engineering principles suggest that the best design is the design that maximizes the system operational effectiveness and at the same time minimizes the total cost of ownership (tco...

This paper describes ILP-PLAN, a framework for solving AI planning problems represented as integer linear programs. ILP-PLAN extends the planning as satisfiability framework to handle plans with resources, action costs, and complex objective functions. We show that challenging planning problems can be effectively solved using both traditional branch-and-bound integer programming solvers and eff...