The multiple traveling salesman problem (mTSP) is a generalization of the well-known traveling salesman problem (TSP), where more than one salesman is allowed to be used in the solution. Moreover, the characteristics of the mTSP seem more appropriate for real-life applications, and it is also possible to extend the problem to a wide variety of vehicle routing problems (VRPs) by incorporating some additional side constraints. Although there exists a wide body of the literature for the TSP and the VRP, the mTSP has not received the same amount of attention. The purpose of this survey is to review the problem and its practical applications, to highlight some formulations and to describe exact and heuristic solution procedures proposed for this problem.

The multiple traveling salesman problem : an overview of formulations and solution procedures

http://egon.cheme.cmu.edu/Papers/BatchReviewMendezGrossmann.pdf

State-of-the-art review of optimization methods for short-term scheduling of batch processes

Job-shop scheduling with blocking and no-wait constraints

A review of planning and scheduling systems and methods for integrated steel production

This paper studies a challenging problem of dynamic scheduling in steelmaking-continuous casting (SCC) production. The problem is to re-optimize the assignment, sequencing, and timetable of a set of existing and new jobs among various production stages for the new environment when unforeseen changes occur in the production system. We model the problem considering the constraints of the practical technological requirements and the dynamic nature. To solve the SCC scheduling problem, we propose an improved differential evolution (DE) algorithm with a real-coded matrix representation for each individual of the population, a two-step method for generating the initial population, and a new mutation strategy. To further improve the efficiency and effectiveness of the solution process for dynamic use, an incremental mechanism is proposed to generate a new initial population for the DE whenever a real-time event arises, based on the final population in the last DE solution process. Computational experiments on randomly generated instances and the practical production data show that the proposed improved algorithm can obtain better solutions compared to other algorithms.

An Improved Differential Evolution Algorithm for Practical Dynamic Scheduling in Steelmaking-Continuous Casting Production

A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex

A mathematical programming model for scheduling steelmaking-continuous casting production

Iron and steel production is a multistage process. A slab yard serves as a storage buffer between the continuous casting stage and the steel rolling mill. Slabs from continuous casting are stacked in the yard to await rolling. When implementing the rolling production schedule, slabs need to be picked up from the slab yard one by one according to the scheduled rolling sequence, heated in the heating furnace and then rolled. There are usually a number of suitable candidate slabs in the yard satisfying the requirement for each rolling item. In general, these candidate slabs are not at the most convenient positions in the stacks. To pick up a required slab, the slabs above it need to be shuffled. To save slab-handling cost and prevent the handling cranes from becoming a bottleneck, slabs for a rolling schedule must be selected from among the candidate slabs so that the total number of slabs shuffled is minimized. The paper studies the slab stack-shuffling problem using the hot strip rolling mill in Shanghai B...

Modelling and a genetic algorithm solution for the slab stack shuffling problem when implementing steel rolling schedules

Steel production is a multi-stage process. A slab yard serves as a buffer between the continuous casting stage and the steel rolling stage. Steel slabs are stored in stacks in the yard. Shuffling is needed when picking up a slab for heating and rolling, if it is not in the top position of a stack. This paper studies the problem of selecting appropriate slabs in the yard for a given rolling schedule so as to minimise the total shuffling cost. The study uses the hot strip rolling mill in Shanghai Baoshan Iron and Steel Complex as an application background. We propose a new heuristic algorithm to solve the problem. This is a two-phase algorithm that first generates an initial feasible solution and then improves it using local search. The new algorithm is compared with the algorithm in use on randomly generated test problems and on real data. Experimental results show that the proposed algorithm yields significant better solutions. The average improvement over the old algorithm is 15%.

Zihou Yang

Papers

A review of planning and scheduling systems and methods for integrated steel production

A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex

A mathematical programming model for scheduling steelmaking-continuous casting production

Modelling and a genetic algorithm solution for the slab stack shuffling problem when implementing steel rolling schedules

An effective heuristic algorithm to minimise stack shuffles in selecting steel slabs from the slab yard for heating and rolling