Ahmed Kouider

This paper addresses a bi-objective scheduling problem modeled as a graph multicoloring problem with a conflict graph. The problem involves scheduling preemptive jobs on parallel machines with the dual objectives of maximizing the total gain of scheduled jobs and minimizing the total completion time of completed jobs. To solve this problem, we propose a Bi-objective Tabu Search (BITS) algorithm, which simultaneously explores multiple solutions, thereby enhancing the search for high-quality non-dominated solutions. BITS is compared with an adapted version of NSGA-II, a widely used algorithm for multi-objective optimization. Extensive computational experiments on benchmark instances demonstrate that BITS consistently outperforms NSGA-II, particularly for large and complex instances, providing an efficient approach for solving the considered bi-objective preemptive scheduling problems.

This paper presents an efficient motion control approach for indoor mobile robots in both static and dynamic workspaces. The proposed system consists of two layers. In the Optimization Layer (Global planner), a Deterministic Constructive Algorithm (DCA) generates the best path for the mobile robot, represented as a set of nodes, to move from the initial position (Source) to the final position (Target) while avoiding the static obstacles. The Control layer (Local planner), which is the main focus of this article, consists of an Efficient Fuzzy-Logic Controller (EFLC), mimicking the human reasoning, to avoid the dynamic obstacles and drive safely the mobile robot along the generated path. The strength of the proposed EFLC approach is shown using V-REP software in dynamic workspaces.

This paper deals with one of the most challenging decisional problems in multi-robot based production systems. It is related to tasks (products) scheduling, which requires the allocation of operations and their sequencing on the robots, while satisfying tasks and robots constraints under makespan minimization.

Graph coloring is one of the most studied combinatorial optimization problems that can be used to model several practical problems. This paper develops a reduction of job shop scheduling problem with unit-time operations to mixed graph coloring. In this study, a methodology based on Mixed Integer Linear Programming and tabu search (TS) algorithm are proposed for solving mixed graph coloring. The performances of the proposed methods are evaluated through several adapted Benchmarks.

We consider the job shop scheduling problem with unit-time operations and the makespan criterion. This problem is reduced to finding an optimal colouring of a special class of mixed graph, where its partial graph without edges represents the union of maximal directed paths and its partial graph without arcs represents the union of maximal cliques. As the problem is known to be NP-hard, both exact and heuristic methods are proposed to solve it. This study is carried out in three steps. First, a new lower and upper bounds for the mixed chromatic number are proposed. Afterwards, a colour-indexed mathematical model using the proposed bounds is developed. Then, a tabu search using a dynamic neighbourhood structure is adapted for solving large instances. Computational experiments conducted on several modified benchmarks show the efficiency and effectiveness of the proposed resolution methods.

In this paper, a distributed multi-agent scheduling system (MASS) based on co-operative approach is proposed to solve static and dynamic job shop scheduling problems (JSSP). The proposed system is composed of two kinds of agents, Supervisor agents and Resource agents. The Supervisor agent decomposes JSSP into interrelated sub-problems and the Resource agents co-operate, through a distributed approach of local idle time minimisation, to solve this problem which is known as one of the most difficult NP-hard problems. Computational results are presented to show the efficiency of MASS in static job shop scheduling. Then, a comparison of the computational results between MASS and some common dispatching rules, on dynamic job arrivals, is studied in terms of effectiveness and stability. Finally, the developed system is validated within an illustrative example, to demonstrate the feasibility of MASS.